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Search results for: GRAPHIC TRAIN TIMETABLE
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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The process of identification of the track's geometrical layout and the alignment project based on the of satellite measurements
PublicationIn the paper a methodology of restoring of railway track’s geometrical shape in a horizontal plane on the base of conducted mobile satellite surveying was presented. The authors proposed a calculating algorithm for designing the track sections placed in horizontal arcs. In the algorithm an analytical methodology with mathematical formulas is applied. The procedure has an universal character, i.e. provides the possibility of varying...
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Satellite inventory of tram track geometrical layout
PublicationIn the paper a methodology of restoring of railway track’s geometrical shape in a horizontal plane on the base of conducted mobile satellite surveying was presented. The authors proposed a calculating algorithm for designing the track sections placed in horizontal arcs. In the algorithm an analytical methodology with mathematical formulas is applied. The procedure has an universal character, i.e. provides the possibility of varying...
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Mobile satellite measurements in designing and exploitation of rail roads
PublicationThe article presents a summary of several years (2009-2015) of studies on the application of mobile satellite Global Navigation Satellite Systems (GNSS) measurements in the field of designing and operation of railways. These studies have been conducted by an interdisciplinary research team from the Gdansk University of Technology and the Gdynia Maritime University. Mobile satellite GNSS measurements are taken during a ride (through...
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BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublicationDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Automatic singing quality recognition employing artificial neural networks
PublicationCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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Between autonomy and paternalism: Attitudes of nursing personnel towards Jehovah’s Witnesses’ refusal of blood transfusion
PublicationObjectives: The study describes the attitudes of Polish nursing personnel towards Jehovah’s Witnesses’ (JWs’) refusal to receive blood and blood products.Methods: We developed an online survey assessing nurses’ knowledge and attitudes towards JWs’ refusal of blood transfusion in a life-threatening condition. It also examined nurses’ attitudes towards ethical and legal issues associated with JWs’ refusal of bloodtransfusions....
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Personalized nutrition in ageing society: redox control of major-age related diseases through the NutRedOx Network (COST Action CA16112)
PublicationA healthy ageing process is important when it is considered that one-third of the population of Europe is already over 50 years old, although there are regional variations. This proportion is likely to increase in the future, and maintenance of vitality at an older age is not only an important measure of the quality of life but also key to participation and productivity. So, the binomial “nutrition and ageing” has different aspects...
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Potential reduction of traffic noise by the means of increased fleet of electric vehicles using a combination of low-noise tyres and low-noise road surfaces
PublicationIn the future, the number of zero-emission vehicles like electric and plug-in hybrid vehicles (in electric mode) is expected to be a substantial part of the vehicle fleet. In Norway, such vehicles already account for approximately 20 % of all new cars sold. Since these vehicles emit negligible noise related to the power-train, the tyre/road noise is the dominating noise source. In the LEO project, tyres designed for such cars have...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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VREA PROJECT - A DIGITAL CURATOR FOR ARCHITECTURE AND DIGITAL PERSPECTIVES FOR HERITAGE MANAGEMENT AND ENHANCEMENT
PublicationThinking about architectural education, one must face the challenges of the ever-changing and digital world and bear in mind the figure of the architect of the future - the curator of digital data. Nowadays the aim is to train specialists who know how to manage the production of digital products and are able to face the challenges of digital change in the field of architecture and architectural heritage management. Virtual Reality...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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Research project BRIK: development of an innovative method for determining the precise trajectory of a railway vehicle
PublicationIn the paper the essential assumptions regarding a research project implemented by a consortium of Gdansk University of Technology and Gdynia Maritime University are presented. The project has been commissioned by National Center of Research and Development with cooperation with Polish Railways (PKP Polskie Linie Kolejowe S.A.). The project is focused in implementation of modern measurement techniques using Global Navigation Positioning...
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The Technological Advancement of New Products, Product Newness and Market Information
PublicationThe purpose of this study is to propose product newness and obtaining market information as mediators of the relationship between the technological advancement of a new product and its commercial success. So far, little is known about the mediators of this relationship but knowledge about the factors that strengthen or weaken it is valid, both for the theory and practice of new product management. On the one hand, product newness...
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublicationBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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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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Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
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Architekturführer Danzig: Gdansk Sopot Gdynia
PublicationIm Zweiten Weltkrieg bis auf die Grundmauern zerstört, wurde der historische Stadtkern der Hansestadt Danzig als polnisches Gdańsk wiederaufgebaut – ein Paradebeispiel für kritische Rekonstruktion in Polen und zugleich eine bis heute stark umstrittene Entscheidung. Zusammen mit dem mondänen Seebad Sopot und der modernen Hafenstadt Gdynia bildet die Bernsteinstadt eine Metropolregion an der polnischen Ostseeküste: die Dreistadt...
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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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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Behavioral state classification in epileptic brain using intracranial electrophysiology
PublicationOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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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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Zastosowanie metody studium przypadku w kształceniu menedżerów
PublicationKształcenie z wykorzystaniem metod rozwiązywania problemów (problem-based learning) staje się coraz bardziej popularne na wszystkich poziomach kształcenia, również w edukacji biznesowej. Przykładem takiej metody jest studium przypadku (case study). Metoda studium przypadku pozwala na rozwijanie umiejętności i kompetencji wykorzystywanych przez menedżerów w ich pracy, np. umiejętności syntezy, identyfikacji problemów, czy podejmowania...
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Multimodal learning application with interactive animated character. [Multimodalna aplikacja edukacyjna wykorzystująca interaktywną animowaną postać]
PublicationThe aim of this study is to design a computer application that may assist teachers and therapists in multimodal manner in their work with impaired or disabled children. The application can be operated in many different ways, giving to a child with special educational needs a possibility to learn and train many skills or treat speech disorders. The main stress in this research is on the creation of animated character that will serve...
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Możliwości zastosowania zasobnikowych jednostek trakcyjnych na liniach kolejowych na przykładzie Pomorskiej Kolei Metropolitalnej
PublicationW artykule zwrócono uwagę, że zasobniki stosowane głównie do rekuperacji energii, mogą być również wykorzystane do zasilania pociągów na niezelektryfikowanych i zelektryfikowanych odcinkach linii kolejowych. Innowacyjność tego rozwiązania wykazano na podstawie dwóch aplikacji kolejowych elektrycznych zasobnikowych jednostek trakcyjnych: pierwszej funkcjonującej od 2014 roku na linii Utsunomiya – Karasuyama w Japonii oraz drugiej,...
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Historic railway stations, documentation and revitalization of the railway infrastructure facilities - protection of cultural and social heritage
PublicationThe article presents problems of documentation and adaptation of buildings which constitute the cultural heritage of the railway infrastructure facilities in Pomerania in Poland. Shows the potential and possibilityto be adopted for various purposes. This problem affects many sites and buildings, railway stations, railway warehouses, residential buildings, technical buildings, water towers, trackman shelters, bridges, viaducts,...
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Collaborative urban studios in Poland. Teaching collective problem solving via live projects
PublicationThe requirements of contemporary architectural and urban design practice places a growing importance on the ability to generate new solutions to complex design challenges. Such an approach is particularly relevant in the context of contemporary urban projects in need of urban innovation and socially engaged practice, i.e. urban regeneration or street quality improvement projects. Meaningful involvement in such topics requires a...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Projekt badawczy BRIK: Opracowanie innowacyjnej metody wyznaczania precyzyjnej trajektorii pojazdu szynowego
PublicationW artykule przedstawiono podstawowe informacje dotyczące projektu badawczego realizowanego na zlecenie Narodowego Centrum Badań i Rozwoju oraz Spółki PKP Polskie Linie Kolejowe S. A. przez Konsorcjum Politechniki Gdańskiej i Uniwersytetu Morskiego w Gdyni. Projekt obejmuje wykorzystanie nowoczesnych metod pomiarowych, takich jak techniki pozycjonowania satelitarnego GNSS, pomiary inercyjne INS oraz skaning laserowy LS, w procesie...
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Using water sources extent during inundation as a reliable predictor for vegetation zonation in a natural wetland floodplain
PublicationDistinctive zones of inundation water during floods were shown to originate from different sources in some major floodplains around the world. Recent research showed that the zonation of water in rivers and floodplains is related to vegetation patterns. In spite of this, water source zones were not used for vegetation modeling due to difficulties in their delineation. In this study, we used simulation results of a fully-coupled...
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Wpływ przechyłki na zjawisko postępowania zużycia bocznego szyn kolejowych w łukach poziomych
PublicationDegradacja elementów nawierzchni kolejowej jest zagadnieniem bardzo złożonym, w które uwikłane jest wiele czynników związanych między innymi z układem geometrycznym toru kolejowego, właściwościami trybologicznymi poszczególnych elementów nawierzchni, jak również z parametrami podłoża gruntowego, a także z właściwościami samych pojazdów szynowych. W artykule omówiono jeden z powyższych problemów, tj. wpływ ukształtowania toru kolejowego...