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Search results for: FACIAL RECOGNITION, DROWSINESS, REAL-TIME MONITORING, MACHINE LEARNING, NEURAL NETWORKS, DRIVER, FATIGUE
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Recognition of hazardous acoustic events employing parallel processing on a supercomputing cluster . Rozpoznawanie niebezpiecznych zdarzeń dźwiękowych z wykorzystaniem równoległego przetwarzania na klastrze superkomputerowym
PublicationA method for automatic recognition of hazardous acoustic events operating on a super computing cluster is introduced. The methods employed for detecting and classifying the acoustic events are outlined. The evaluation of the recognition engine is provided: both on the training set and using real-life signals. The algorithms yield sufficient performance in practical conditions to be employed in security surveillance systems. The...
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Cost minimization in wireless networks with a bounded and unbounded number of interfaces
PublicationPraca dotyczy problemu minimalizacji energii poprzez selektywne odłączanie urządzeń komunikacyjnych w wielointerfejsowych sieciach bezprzewodowych w taki sposób, by zapewnić realizację wymaganego grafu połączeń. Sformułowano problem optymalizacyjny, podano wyniki dotyczące jego trudności i zaproponowano algorytmy optymalizacyjne. Rozważono zarówno wariant, w którym liczba interfejsów komunikacyjnych jest parametrem stałym (narzuconym...
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Contextual Knowledge to Enhance Workplace Hazard Recognition and Interpretation in a Cognitive Vision Platform
PublicationThe combination of vision and sensor data together with the resulting necessity for formal representations builds a central component of an autonomous Cyber Physical System for detection and tracking of laborers in workplaces environments. This system must be adaptable and perceive the environment as automatically as possible, performing in a variety of plants and scenes without the necessity of recoding the application for each...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Adrian Bekasiewicz dr hab. inż.
PeopleAdrian Bekasiewicz received the MSc, PhD, and DSc degrees in electronic engineering from Gdansk University of Technology, Poland, in 2011, 2016, and 2020, respectively. In 2014, he joined Engineering Optimization & Modeling Center where he held a Research Associate and a Postdoctoral Fellow positions, respectively. Currently, he is an Associate Professor with Gdansk University of Technology, Poland. His research interests include...
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Gesture recognition framework for multimedia content viewer controlling
PublicationIn the paper a system for controlling a multimedia content viewer by hand gestures is presented. First, selected methods used for gesture recognition are described. Two different application cases of the system, i.e. for multimedia presentation purposes and for multimedia content viewing are outlined. Moreover, a proposal of improvement of the system combining these approaches is also given. The system work cycle is reviewed. The...
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Monitoring of single-side lap grinding with electroplated tools
PublicationThe results presented in the paper show that utilising microphones as audible sound sensors is a suitable approach for monitoring a single-side lap grinding process due to the low levels of noise generated by the drives of a machine tool. The results confirm that sound signal analysis is a feasible and relatively simple method to monitor a lap grinding process with the use of an audible sound sensor. Proposed method can be used...
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Fatigue-Biomedicine Health and Behavior
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublicationExpert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...
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Bimodal classification of English allophones employing acoustic speech signal and facial motion capture
PublicationA method for automatic transcription of English speech into International Phonetic Alphabet (IPA) system is developed and studied. The principal objective of the study is to evaluate to what extent the visual data related to lip reading can enhance recognition accuracy of the transcription of English consonantal and vocalic allophones. To this end, motion capture markers were placed on the faces of seven speakers to obtain lip...
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublicationIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
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Investigating the Effects of Geometrical Parameters of Re-Entrant Cells of Aluminum 7075-T651 Auxetic Structures on Fatigue Life
PublicationIn this study, the effects of two geometrical parameters of the re-entrant auxetic cells, namely, internal cell angle (θ) and H/L ratio in which H is the cell height, and L is the cell length, have been studied on the variations of Poisson’s ratio and fatigue life of Aluminum 7075-T6 auxetic structures. Five different values of both the H/L ratio and angle θ were selected. Numerical simulations and fatigue life predictions have...
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Correlation between Fractal Dimension and Areal Surface Parameters for Fracture Analysis after Bending-Torsion Fatigue
PublicationThis paper investigates the fracture surface topography of two steel and aluminum alloys subject to bending-torsion fatigue loadings, as well as their susceptibility to fatigue performance and failure mechanisms. Using fracture surface topography data analysis, elements with different geometries were elaborated. A correlation between the fractal dimension, other selected parameters of surface topography such as areal Sx, and...
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Blended Learning in Teaching Safety of Electrical Installations
PublicationBlended learning becomes more commonly used in teaching information technology or other subjects, which involve practice in computer laboratories. In case of subjects with no access to computer rooms blended learning supports lecturing and teaching classes e.g. interactive lessons. The article presents the use of blended learning forms in Gdansk University of Technology in teaching the subject of Safety of Electrical Installations....
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Comparison of edge detection algorithms for electric wire recognition
PublicationEdge detection is the preliminary step in image processing for object detection and recognition procedure. It allows to remove useless information and reduce amount of data before further analysis. The paper contains the comparison of edge detection algorithms optimized for detection of horizontal edges. For comparison purposes the algorithms were implemented in the developed application dedicated to detection of electric line...
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Disaster Resilience of Optical Networks: State of the Art, Challenges, and Opportunities
PublicationFor several decades, optical networks, due to their high capacity and long-distance transmission range, have been used as the major communication technology to serve network traffic, especially in the core and metro segments of communication networks. Unfortunately, our society has often experienced how the correct functioning of these critical infrastructures can be substantially hindered by massive failures triggered by natural...
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A Highly Scalable, Modular Architecture for Computer Aided Assessment e-Learning Systems
PublicationIn 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...
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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublicationPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Overview of Scalability and Reliability Problem in SDN Networks
PublicationIn the paper an overview of scalability and reliability in the SDN (Software Defined Networks) networks has been presented. Problems and limitations for guaranteeing scalability and reliability in SDN networks have been indicated. Known methods for assuring scalability and reliability in SDN networks have been described. Projects from research communities for resolving issues with scalability and reliability in SDN networks have...
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The reliability of tree and star networks
PublicationThis paper investigated the reliability of tree and star networks. Following measures of network reliability are assumed: the expected number of nodes, that can communicate with the central node; the expected number of node pairs, that are connected by a path through the central node; the expected number of node pairs communicating.
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Protection in elastic optical networks
PublicationIn this article, we analyze gains resulting from the use of EON architectures with special focus on transportation of cloud-ready and content-oriented traffic in the context of network resilience. EONs are a promising approach for future optical transport networks and, apart from improving the network spectral efficiency, bring such new capabilities as squeezed protection, which reduces resource requirements in failure scenarios....
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Optical recognition elements: macrocyclic imidazole chromoionophores entrapped in silica xerogel
PublicationMaterials containing new chromoionophores consisting of crown residue and azole moiety as partsof macrocycles were encapsulated by the sol-gel procedure in silica xerogel matrices and proposed aschemical recognition elements especially for such metal ions as Li+, Cs+ and Cu2+. Action of these recognition elements is in principle based on changes of reflectance. The recognition elements containing 21-membered chromogenic...
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Service-based Resilience for Embedded IoT Networks
PublicationEmbedded IoT networks are the backbone of safety-critical systems like smart factories, autonomous vehicles, and airplanes. Therefore, resilience against failures and attacks should be a prior concern already in their design stage. In this study, we introduce a service-based network model as an MILP optimization problem for the efficient deployment of a service overlay to the embedded network by meeting QoS and resilience requirements....
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2022 MICROSCOPY IN ENVIRONMENTAL MONITORING -lecture - Nowy
e-Learning CoursesThe online repository will be used to teach students by presenting them lectures about variable aspects of microscopy techniques used in environmental monitoring.
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Polynomial Algorithm for Minimal (1,2)-Dominating Set in Networks
PublicationDominating sets find application in a variety of networks. A subset of nodes D is a (1,2)-dominating set in a graph G=(V,E) if every node not in D is adjacent to a node in D and is also at most a distance of 2 to another node from D. In networks, (1,2)-dominating sets have a higher fault tolerance and provide a higher reliability of services in case of failure. However, finding such the smallest set is NP-hard. In this paper, we...
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Container monitoring system
PublicationW pracy przedstawiono koncepcję systemu monitorowania kontenerów przewożonych drogą morską. Scharakteryzowano główne cechy oraz przedstawiono modułowo-warstwowy schemat funkcjonalny. Ponadto opisano założenia funkcjonalno-użytkowe dotyczące Inteligentnego Modułu Kontenerowego (SCM), będącego podstawowym elementem składowym systemu. Przedstawiono również główne zadania projektowe związane z realizacją projektu
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Computer Networks - lectures 2024/2025
e-Learning CoursesStudent uczy się: jak mówić o sieciach komputerowych - poznaje podstawowe pojęcia (np. protokół komunikacyjny), ich znaczenie i związki; jak sieci komuterowe są zbudowane i wykorzystywne - uczy się podstaw działania sieci (np. komutacja pakietów) i architektury sieci (np. płaszczyzny sieci) oraz poznaje podstawowe technologie sieciowe (np. protokół IP); jak sieci komputerowe ewoluują - poznaje historię rozwoju sieci, ewolucję wymagań,...
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Laser Beam as a Precision Tool to Increase Fatigue Resistance in an Eyelet of Undercarriage Drag Strut
PublicationThe article contains the results of tests on a laser-processed eyelet of undercarriage drag strut to increase its fatigue strength. Laser processing concentrated on both sides around the hole of eye for connecting the undercarriage drag strut caused that the material in this area withstood more than twice the number of load cycles established for this material. In order to determine the reasons for the increase in fatigue strength,...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Method of Monitoring of the Grinding Process with Lapping Kinematics Using Audible Sound Analysis
PublicationUtilising microphones as audible sound sensors for monitoring a single-side grinding process with lapping kinematics is presented in the paper. The audible sound generated during grinding depended on the cutting properties of electroplated tools with D107 diamond grains and different thicknesses of the nickel bond. The tool wear affected the obtained technological effects such as material removal rate and the surface roughness...
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THE UNSUSTAINABILITY OF PUBLIC-SECTOR ORGANIZATIONAL NETWORKS: A CASE STUDY OF VOLUNTARY COURT NETWORKS
PublicationPurpose: The purpose of this study is to identify the problem of sustainability of public-sector 12 organizational networks on the example of common courts and what it implies for further 13 research. Methodology: The study used qualitative research tools in the form of structured 14 interviews. Interviews were conducted with 36 presidents and directors of common courts. 15 After conducting and transcribing each interview, their...
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Innovative e-learning approach in teaching based on case studies - Innocase project
PublicationThe article presents the application of innovative e-learning approach for the creation of case study content. Case study methodology is becoming more and more widely applied in modern education, especially in business and management field. Although case study methodology is quite well recognized and used in education, there are still few examples of developing e-learning content on the basis of case studies. This task is to be...
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublicationIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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Emotion Recognition
Open Research DataThe films presented here were recorded using so-called high-speed camera Phantom Miro. To play the movie You need the special software which can be downloaded from the web site https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware the details of the movie are available after starting the movie in the viewer in the description...
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Emotion Recognition
Open Research DataThe films presented here were recorded using so-called high-speed camera Phantom Miro. To play the movie You need the special software which can be downloaded from the web site https://www.phantomhighspeed.com/resourcesandsupport/phantomresources/pccsoftware the details of the movie are available after starting the movie in the viewer in the description...
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Fatigue resistance investigation of the IC engine MB11 bearings, working under conditions of dynamic unidirectional loadings
PublicationThe slide bearing material MB11 fatigue resistance has been investigated with the application of SMOK - test stand in which dynamic unidirectional loadings to the test bearing is generated. Slide bearing layer consists of the bronze MB11 ( Cu Pb22 Sn 3 ) sintered to the steel shell. Each of the tested bearing has been subject to the standard 20-hour test, under conditions of the full fluid lubrication. Methodology of the experiments,...
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Analysis of effect of overloaded vehicles on fatigue life of flexible pavements based on weigh in motion (WIM) data
PublicationOverloaded vehicles have a significant impact on pavement fatigue life and distress. As the studies show, the phenomena intensify when the control of traffic is poor. The paper presents the results of the research including analysis of weigh in motion data from eight stations and analysis of asphalt pavement fatigue caused by mixed traffic. Distributions of vehicles axles load including the multiple axles effects are presented....
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Performance of LSP preemption methods in different MPLS networks
PublicationPreemption in Multiprotocol Label Switching (MPLS) is an optional traffic engineering technique used to create a new path of high priority when there is not enough bandwidth available. In such case the path is admitted by removing one or more previously allocated paths of lower priority. As there are usually many possible sets of low priority paths which can be selected, a preemption algorithm is being started to select the best...
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A Review of Traffic Analysis Attacks and Countermeasures in Mobile Agents' Networks
PublicationFor traditional, message-based communication, traffic analysis has been already studied for over three decades and during that time various attacks have been recognised. As far as mobile agents’ networks are concerned only a few, specific-scope studies have been conducted. This leaves a gap that needs to be addressed as nowadays, in the era of Big Data, the Internet of Things, Smart Infrastructures and growing concerns for privacy,...
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Electrical and noise responses of carbon nanotube networks enhanced by UV light for detection of organic gases (ethanol, acetone)
Open Research DataCarbon nanotube networks of different optical transparencies were investigated via resistance and 1/f noise measurements for detection of ethanol and acetone. The sensor resistive and noise responses were collected for dark and UV-assisted conditions, revealing the improvement in sensor sensitivity and limit of detection after applying UV light (275...
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Residence time distribution in rapid multiphase reactors
PublicationResidence time distribution (RTD) provides information about average hydraulic residence time and the distribution of material in the reactor. A method for determining RTD for reactors with very short hydraulic residence times is deconvolution based on extraction of real RTD by the analysis of a non-ideal input signal. The mean residence time and dispersion were determined for the spinning fluids reactor (SFR). For the first time...
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Federated Learning in Healthcare Industry: Mammography Case Study
PublicationThe paper focuses on the role of federated learning in a healthcare environment. The experimental setup involved different healthcare providers, each with their datasets. A comparison was made between training a deep learning model using traditional methods, where all the data is stored in one place, and using federated learning, where the data is distributed among the workers. The experiment aimed to identify possible challenges...
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Scoreboard Architectural Pattern and Integration of Emotion Recognition Results
PublicationThis paper proposes a new design pattern, named Scoreboard , dedicated for applications solving complex, multi-stage, non-deterministic problems. The pattern provides a computational framework for the design and implementation of systems that integrate a large number of diverse specialized modules that may vary in accuracy, solution level, and modality. The Scoreboard is an extension of Blackboard design pattern and comes under...
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Exploiting Multi-Interface Networks: Connectivity and Cheapest Paths
PublicationRozważano zagadnienie minimalizacji energii w sieciach bezprzewodowych bez infrastruktury, w których niektóre węzły są wyposażone w więcej, niż jeden interfejs. W przyjętym modelu sieci podano nowe algorytmy przybliżone oraz wyniki dotyczące złożoności obliczeniowej dla dwóch problemów: aktywacji najtańszej spójnej podsieci spinającej oraz aktywacji ścieżki pomiędzy ustaloną parą węzłów.
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An efficient approach to optimization of semi‐stable routing in multicommodity flow networks
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Will NILM Technology Replace Multi-Meter Telemetry Systems for Monitoring Electricity Consumption?
PublicationThe estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublicationThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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