Search
Search results for: GRAPHIC TRAIN TIMETABLE
-
Shape-Based Pose Estimation of Robotic Surgical Instruments
PublicationWe describe a detector of robotic instrument parts in image-guided surgery. The detector consists of a huge ensemble of scale-variant and pose-dedicated, rigid appearance templates. The templates, which are equipped with pose-related keypoints and segmentation masks, allow for explicit pose estimation and segmentation of multiple end-effectors as well as fine-grained non-maximum suppression. We train the templates by grouping examples...
-
Practical Eco-Driving Strategy for Suburban Electric Multiple Unit
PublicationIn this paper, a practical approach to velocity profile optimization for electric multiple unit was presented. The study focuses on a case of fast urban railway, which is a popular mean of transport across Tricity, Poland. Based on observations and measurements, a potential for improvement of energy efficiency by modifying the speed profile was recognized. In order to conduct necessary calculations, simulation model of railway...
-
Cross-Lingual Knowledge Distillation via Flow-Based Voice Conversion for Robust Polyglot Text-to-Speech
PublicationIn this work, we introduce a framework for cross-lingual speech synthesis, which involves an upstream Voice Conversion (VC) model and a downstream Text-To-Speech (TTS) model. The proposed framework consists of 4 stages. In the first two stages, we use a VC model to convert utterances in the target locale to the voice of the target speaker. In the third stage, the converted data is combined with the linguistic features and durations...
-
Numeryczna analiza dynamiczna wieszaków w łukowym wiadukcie kolejowym. Analiza przypadku
PublicationW artykule przedstawiono analizę dynamiczną wiaduktu kolejowego w ciągu Centralnej Magistrali Kolejowej zlokalizowanego koło Huty Zawadzkiej. W analizie zwrócono szczególną uwagę na lokalną odpowiedź wieszaków na obciążenie przejeżdżającym pociągiem oraz wiatrem. Obliczenia przeprowadzono na podstawie wykonanego modelu MES. Zweryfikowano poprawność modelu poprzez porównanie uzyskanych wyników z wartościami pomierzonymi. Przeprowadzono...
-
Adversarial attack algorithm for traffic sign recognition
PublicationDeep learning suffers from the threat of adversarial attacks, and its defense methods have become a research hotspot. In all applications of deep learning, intelligent driving is an important and promising one, facing serious threat of adversarial attack in the meanwhile. To address the adversarial attack, this paper takes the traffic sign recognition as a typical object, for it is the core function of intelligent driving. Considering...
-
Detecting type of hearing loss with different AI classification methods: a performance review
PublicationHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
-
Jakub Jabłoński inż.
PeopleEducation In 2016 Jakub Jabłoński finished Zbigniew Herbert XX High School in Gdańsk (math-physics-IT profile). In 2017 he started an undergraduate course in Civil Engineering at the Faculty of Civil and Environmental Engineering of the Gdańsk University of Technology, which he graduated in 2021 with the title of Bachelor of Science in Engineering. During his studies he took active part in the scientific association "Hevelius". Employment About...
-
Efficient uncertainty quantification using sequential sampling-based neural networks
PublicationUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
-
Mask Detection and Classification in Thermal Face Images
PublicationFace masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
-
Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
-
Spiral Search Grasshopper Features Selection with VGG19-ResNet50 for Remote Sensing Object Detection
PublicationRemote sensing object detection plays a major role in satellite imaging and is required in various scenarios such as transportation, forestry, and the ocean. Deep learning techniques provide efficient performance in remote sensing object detection. The existing techniques have the limitations of data imbalance, overfitting, and lower efficiency in detecting small objects. This research proposes the spiral search grasshopper (SSG)...
-
DevEmo—Software Developers’ Facial Expression Dataset
PublicationThe COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...
-
A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
-
Exploring thiophene-2-acetate and thiophene-3-acetate binding modes towards the molecular and supramolecular structures and photoluminescence properties of Pb(ii) polymers
PublicationTo evaluate the impact of the flexible positional isomeric ligands thiophene-2-acetate (2tpacCOO) andthiophene-3-acetate (3tpacCOO) on the construction and self-assembly process of Pb(II) polymers, twonovel compounds, [Pb(2tpacCOO)2(H2O)]n(1) and [Pb(3tpacCOO)2]n(2), were preparedviaanonhydro-thermal method with respect to green chemistry rules. The obtained polymers were fully characterized byelemental analysis, TG/DTG and PXRD,...
-
Development of an AI-based audiogram classification method for patient referral
PublicationHearing 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...
-
ZINTEGROWANE ZARZĄDZANIE STREFĄ PRZYBRZEŻNĄ ORAZ URBANISTYKA – PROJEKT NOWYCH SPECJALNOŚCI NA KIERUNKU GOSPODARKA PRZESTRZENNA NA POLITECHNICE GDAŃSKIEJ
PublicationNa studiach II stopnia na kierunku gospodarka przestrzenna na Wydziale Architektury Politechniki Gdańskiej w 2017 r. otwierane są dwie specjalności: urbanistyka i zintegrowane zarządzanie strefą przybrzeżną. Trzon programu studiów dla obu specjalności jest wspólny i oparty na dotychczasowych standardach kształcenia na tym kierunku. Specjalność zintegrowane zarządzanie strefą przybrzeżną jest odpowiedzią na konieczność wprowadzenia...
-
Wybrane zagadnienia optymalizacji organizacji ruchu kolejowego w celu minimalizacji kosztów energii elektrycznej
PublicationW artykule przedstawiono podział kosztów w transporcie kolejowym z uwzględnieniem kosztów wewnętrznych przedsiębiorstwa, do których zaliczają się między innymi koszty dostępu do infrastruktury, czy koszty energii. Stwierdzono, że przy odpowiedniej organizacji ruchu pociągów na sieci kolejowej, bez ponoszenia dodatkowych nakładów na infrastrukturę i specjalistyczne urządzenia, można znacznie ograniczyć zużycie energii, a co za tym...
-
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...
-
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...
-
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...
-
Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
-
Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
-
Emission of 1.3–10 nm airborne particles from brake materials
PublicationOperation of transport vehicle brakes makes a significant contribution to airborne particulate matter in urban areas, which is subject of numerous studies due to the environmental concerns. We investigated the presence and number fractions of 1.3–10 nm airborne particles emitted from a low-metallic car brake material (LM), a non-asbestos organic car brake material (NAO) and a train brake cast iron against a cast iron. Particles...
-
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...
-
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...
-
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...
-
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....
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
Nowoczesne metody wizualizacji treści dydaktycznych (szkolenie zewnętrzne)
e-Learning CoursesCEL Podniesienie kompetencji kadry w zakresie stosowania nowoczesnych metod wizualizacji treścidydaktycznych. OPIS Warsztat z zakresu atrakcyjnej wizualizacji treści dydaktycznych. Uczestnicy szkolenia nabędą informacje na temat: technik sketchnoting i graphic facilitation, m.in.: tworzenie banku rysunków, przygotowanie kreatywnych szablonów, praca z metaforą, komponowania wieloformatowego plakatu dostosowanego do konkretnych...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...