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System monitoringu odbieraków prądu pojazdów kolejowych w aspekcie bezpieczeństwa i ciągłości ruchu.
PublicationOmówiono metodę monitorowania stanu technicznego odbieraków prądu w oparciu o pomiar uniesienia przewodów jezdnych sieci trakcyjnej w czasie przejazdu pociągu. Opisano konstrukcję i zasadę działania wdrożonego na linii kolejowej pilotażowego stanowiska monitoringu. Przedstawiono metodę analizy i sposób wizualizacji wyników pomiarów. Zastosowany algorytm szacowania siły statycznej odbieraka uwzględnia prędkości pociągu i działanie...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Autonomous Perception and Grasp Generation Based on Multiple 3D Sensors and Deep Learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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MobileNet family tailored for Raspberry Pi
PublicationWith the advances in systems-on-a-chip technologies, there is a growing demand to deploy intelligent vision systems on low-cost microcomputers. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity of contemporary convolutional neural networks (CNNs). The state-of-the-art lightweight CNN is MobileNetV3. However, it was designed to achieve a good trade-off between...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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How to Sort Them? A Network for LEGO Bricks Classification
PublicationLEGO bricks are highly popular due to the ability to build almost any type of creation. This is possible thanks to availability of multiple shapes and colors of the bricks. For the smooth build process the bricks need to properly sorted and arranged. In our work we aim at creating an automated LEGO bricks sorter. With over 3700 different LEGO parts bricks classification has to be done with deep neural networks. The question arises...
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Performance improvement of NN based RTLS by customization of NN structure - heuristic approach
PublicationThe purpose of this research is to improve performance of the Hybrid Scene Analysis – Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis...
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Analiza wyników monitoringu odbieraków prądu w warunkach ruchowych na linii kolejowej
PublicationOmówiono metodę ciągłego monitorowania stanu odbieraków prądu na linii kolejowej w oparciu o pomiar uniesienia przewodów jezdnych sieci trakcyjnej w czasie przejazdu pociągu. Omówiono zasadę działania wdrożonego stanowiska monitoringu. Opisano algorytmy analizy danych pomiarowych - w szczególności oszacowania siły statycznej odbieraka prądu - i przyjęte kryteria oceny odbieraka. W analizie bierze się pod uwagę także prędkość pociągu...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublicationThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Aleksandra Parteka dr hab. inż.
PeopleAbout me: I am an associate professor and head of doctoral studies at the Faculty of Management and Economics, Gdansk University of Technology (GdanskTech, Poland). I got my MSc degree in Economics from Gdansk University of Technology (2003) and Universita’ Politecnica delle Marche (2005), as well as MA degree in Contemporary European Studies from Sussex University (2006, with distinction). I received my PhD in Economics...
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Performance Analysis of the OpenCL Environment on Mobile Platforms
PublicationToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublicationLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublicationThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublicationThe automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...
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Radio Communication Antennas and MIMO Techniques (2023/24)
e-Learning CoursesCourse assigned to the following subject: - Radio Communication Antennas and MIMO Techniques (profile Radio Communication Systems and Networks [EN])
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Runge-Kutta bicharacteristic methods for first order partial functional di- fferential equations
PublicationW pracy prezentujemy nową klasę metod numerycznych dla równań różniczkowo-funkcyjnych. Są to metody bicharakterystyk Rungego-Kutty. Ponadto porównuje-my wprowadzone metody z metodami klasycznymi.
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Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublicationW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
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Conference on Security and Cryptography for Networks
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IEEE International Conference on Networks
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Embedded Sensor Networks Workshop
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Information Processing in Sensor Networks
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Impact of R/X ratio of distribution network on selection and control of energy storage units
PublicationThe interest in energy storage is still increasing. Energy storage units are installed in high voltage networks, medium voltage networks and low voltage distribution networks as well. These units are often used to improve power quality. One of the criteria for improving power quality is reducing voltage deviations. Depending on the type of network and specifying its R/X ratio, this criterion can be fulfilled by control of active...
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Oddziaływania taboru na mosty kolejowe przy zmiennych parametrach ruchu
PublicationW pracy poruszono zagadnienia związane z identyfikacją oraz modelowaniem układu dynamicznego most-pojazd ruchomy. Za element szczególnie istotny uznano czynnik obciążający. Opracowano i wdrożono metodykę identyfikacji cech dynamicznych rzeczywistego pojazdu szynowego. Eksperyment badawczy przeprowadzono dla jednostki trakcyjnej EN57, jednak nie ma żadnych ograniczeń w stosowaniu metody dla innego, konwencjonalnego taboru szynowego....
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Workshop on Applications of Graph Theory in Wireless Ad hoc Networks and Sensor Networks
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Multi-Option Model of Railway Traffic Organization Including the Energy Recuperation
PublicationThe article presents the issue of organization of railway traffic within the station, taking into account energy recuperation. We identified a number of factors which affect the energy efficiency of recuperation, including the issue of transfer of energy technology between a few vehicles. We presented some aspects of the decision problem of graphic train timetable construction with regard to recuperation. As an indicator of quality...
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublicationThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublicationThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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A new multi-process collaborative architecture for time series classification
PublicationTime 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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Data governance: Organizing data for trustworthy Artificial Intelligence
PublicationThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....
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Rust QA: question answering dataset for "The Rust Programming Language" in SQuAD 2.0 format
Open Research DataRust QA is a dataset for training and evaluating QA systems. The dataset consists of 1068 questions to "The Rust Programming Language" book (https://doc.rust-lang.org/stable/book/) with the answers provided as text spans from the book. The dataset is released in SQuAD 2.0 format.
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Prognostic and diagnostic capabilities of OOBN in assessing investment risk of complex construction projects
PublicationModelling decision problems using Bayesian networks is extremely valuable especially in case of issues related to uncertainty; it is also very helpful in constructing and understanding visual representation of the elements and their relations. This approach facilitates subsequent application of Bayesian networks, however there can be situations where using simple Bayesian networks is impractical or even ineffective. The aim of...
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Olga Błaszkiewicz mgr inż.
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SiC-Based Power Electronic Traction Transformer (PETT) for 3 kV DC Rail Traction
PublicationThe design of rolling stock plays a key role in the attractiveness of the rail transport. Train design must strictly meet the requirements of rail operators to ensure high quality and cost-eective services. Semiconductor power devices made from silicon carbide (SiC) have reached a level of technology enabling their widespread use in traction power converters. SiC transistors oering energy savings, quieter operation, improved reliability...
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Wojciech Siwicki dr inż.
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A Test-Bed Analysis of Simultaneous PMIPv6 Handover in 802.11 WLANs Environment
PublicationProviding mobility in access networks is a challenge that we have to deal with. Due to networks’ convergence and migration to all-IP networks, mobility management at the network layer is required. However, there is a need for cooperation mechanisms between the network layer and lower layers to support multimedia services and make handover more efficient. This paper presents experimental research on simultaneous handover performance...
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Future research directions in design of reliable communication systems
PublicationIn this position paper on reliable networks, we discuss new trends in the design of reliable communication systems. We focus on a wide range of research directions including protection against software failures as well as failures of communication systems equipment. In particular, we outline future research trends in software failure mitigation, reliability of wireless communications, robust optimization and network design, multilevel...
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International Telecommunication Networks and Applications Conference (Australian Telecommunication Networks and Applications Conference [ATNAC])
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Michał Kowalewski dr inż.
PeopleResearch career: Doctoral dissertation "Tolerance robust, dictionary methods of fault diagnosis of electronic circuits with specialized neural classifier". Participation as a performer in four KBN research teams MNiSW and NCBiR concerning the development of diagnostic methods for analog electronic circuits and diagnostics of technical objects using impedance spectroscopy methods. 39 publications, including 10 in magazines,...
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Tacjana Niksa-Rynkiewicz dr inż.
PeopleTacjana Niksa-Rynkiewicz - doctor of science in the field of computer science (2011). The doctoral dissertation concerned issues related to the development of Artificial Intelligence methods, and more precisely the generalization of triangular norms in fuzzy neural systems. Currently, he is a researcher (assistant professor) at the Gdańsk University of Technology. He develops his skills and conducts research in the use of methods...
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Damage Detection Strategies in Structural Health Monitoring of Overhead Power Transmission System
PublicationOverhead power transmission lines, their supporting towers, insulators and other elements create a highly distributed system that is vulnerable to damage. Typical damage scenarios cover cracking of foundation, breakage of insulators, loosening of rivets, as well as cracking and breakage of lines. Such scenarios may result from various factors: groundings, lightning strikes, floods, earthquakes, aeolian vibrations, conductors galloping,...
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Problems of modelling toxic compounds emitted by a marine internal combustion engine for the evaluation of its structure parameters
PublicationThe paper presents the possibility of using an analytical study of the engine exhaust ignition to evaluate the technical condition of the selected components. Software tools available for the analysis of experimental data commonly use multiple regression model that allows the study of the effects and iterations between model input quantities and one output variable. The use of multi-equation models gives a lot of freedom in the...
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Exploring the influence of personal factors on physiological responses to mental imagery in sport
PublicationImagery is a well-known technique in mental training which improves performance efficiency and influences physiological arousal. One of the biomarkers indicating the amount of physiological arousal is skin conductance level (SCL). The aim of our study is to understand how individual differences in personality (e.g. neuroticism), general imagery and situational sport anxiety are linked to arousal measuring with SCL in situational...
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How Can We Identify Electrophysiological iEEG Activities Associated with Cognitive Functions?
PublicationElectrophysiological activities of the brain are engaged in its various functions and give rise to a wide spectrum of low and high frequency oscillations in the intracranial EEG (iEEG) signals, commonly known as the brain waves. The iEEG spectral activities are distributed across networks of cortical and subcortical areas arranged into hierarchical processing streams. It remains a major challenge to identify these activities in...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies
PublicationLeading technologies are very attractive for students preparing their theses as the completion of their studies. Such an orientation of students connected with professional experiences seems to be a crucial motivator in the research in the management and business areas where these technologies condition the development of professional activities. The goal of the paper is the analysis of students’ thesis topics defended in the last...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: 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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Synteza układu sterowania statkiem morskim dynamicznie pozycjonowanym w warunkach niepewności
PublicationNiniejsza monografia obejmuje zagadnienia związane z syntezą układu dynamicznego pozycjonowania statku w środowisku morskim z zastosowaniem wybranych nieliniowych metod sterowania. W ramach pracy autorka rozważała struktury sterowania z zastosowaniem wektorowej adaptacyjnej metody backstep oraz metod jej pokrewnych, takich jak regulatory MSS (ang. multiple surface sliding), DSC (ang. dynamic surface control), NB (ang. neural backstepping)....