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Wyniki wyszukiwania dla: FACIAL RECOGNITION, DROWSINESS, REAL-TIME MONITORING, MACHINE LEARNING, NEURAL NETWORKS, DRIVER, FATIGUE
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Disk space allocation schemes for real-time data gathering applications
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CMOS implementation of an analogue median filter for image processing in real time
PublikacjaAn analogue median filter, realised in a 0.35 μm CMOS technology, is presented in this paper. The key advantages of the filter are: high speed of image processing (50 frames per second), low-power operation (below 1.25 mW under 3.3 V supply) and relatively high accuracy of signal processing. The presented filter is a part of an integrated circuit for image processing (a vision chip), containing: a photo-sensor matrix, a set of...
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International Journal of Embedded and Real-Time Communication Systems
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Marek Krawczuk prof. dr hab. inż.
OsobyKariera naukowa 1987 mgr inż. - absolwent Wydziału Mechanicznego PG 1991 dr inz. - Instytut Maszyn Przepływowych PAN 1995 dr hab. inż. - Instytut Maszyn Przepływowych PAN 2003 prof - Instytut Maszyn Przepływowych PAN Zatrudnienie 1987-89 Politechnika Gdańsk 1989-2007 Instytut Maszyn Przepływowych PAN w Gdańsku 2001-2003 Uniwersytet Warmińsko-Mazurski w Olsztynie 2003 - Politechnika Gdańska
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Measures of region failure survivability for wireless mesh networks
PublikacjaWireless mesh networks (WMNs) are considered as a promising alternative to wired local, or metropolitan area networks. However, owing to their exposure to various disruptive events, including natural disasters, or human threats, many WMN network elements located close to the failure epicentre are frequently in danger of a simultaneous failure, referred to as a region failure. Therefore, network survivability, being the ability...
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E-learning courses
Kursy OnlineStrona zawiera zbiór kursów prowadzonych metodą e-learning. Kursy te są skierowane do studentów I stopnia kierunku informatyka na VII semestrze profilu Bazy danych, do studentów na kierunku informatyka na II semestrze studiów II stopnia na specjalności ZAD i ISI.
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Problems of analytical determination of journal bearing bush fatigue strength estimates
PublikacjaProblems connected with determination of stress distribution in sliding layer of thinwalled bearing bushes, investigated in bearing fatigue test rigs, have been presented. Using an example of plain bearings tested in the fatigue machine SMOK (built at the Gdask University of Technology) problems with obtaining a convergence of iterative procedure for determining the fatigue strength estimators of bearing alloy surface layer are...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublikacjaIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Influence of pitting corrosion on fatigue and corrosion fatigue of ship structures. Part I: pitting corrosion of ship structures.
PublikacjaThe paper is a literature survey focused on pitting corrosion and its influence on fatigue of ship and offshore steels. Mechanisms of short- and long-term pitting corrosion in marine environment have been described including pit nucleation and growth phases. Some models of pit growth versus time of exposure have been presented. Some factors which influence the pit growth have been discussed briefly.
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Fatigue life improvement using low transformation temperature weld material with measurement of residual stress
PublikacjaWelding processes often produce high levels of tensile residual stress. Low transformation temperature (LTT) welding wires utilise phase transformation strains to overcome the thermal contraction of a cooling weld. In this paper, the residual stress within each weld was quantified using the milling/strain gauge method, being the strain change measured as the weldment was milled away. The fatigue tests were conducted under uniaxial...
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3D visualisation and monitoring of marine pollutant aggregations in Web-based GIS
PublikacjaPrzedstawiony internetowy GIS służy do integracji, przetwarzania i wizualizacji pochodzących z wielu źródeł danych o różnych komponentach środowiska morskiego, w tym o zanieczyszczeniach. Jako przykład przedstawiono wyniki trójwymiarowego modelowania rozprzestrzeniania się wylewu olejowego w morzu.
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Quasistatic and fatigue behavior of an AISI H13 steel obtained by additive manufacturing and conventional method
PublikacjaThis work aims to compare the mechanical behavior of an AISI H13 steel obtained by additive manufacturing with that obtained by conventional manufacturing methods. The average values of the ultimate tensile strength (UTS) and ductility obtained for the specimens produced by the conventional method were equal to 658 MPa and 18%, respectively, which compares with 503 MPa and 0.75% registered for the selective laser melting (SLM)...
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Molecular and chemical monitoring of growth and Ochratoxin A biosynthesis of P. verrucosum in wheat stored at different moisture conditions
PublikacjaDoświadczenie polegało na obserwacji wzrostu P. verrucosum na ziarnach pszenicy, składowanej w różnych warunkach (wilgotność, temperatura) oraz zdolności do produkcji Ochratoksyny A (OTA) przez tę pleśń. Wzrost mierzony był w jednostkach tworzących kolonie (cfu colony forming units). Biosynteza OTA kontrolowana była przy pomocy HPLC, a ekspresja genu otapksPV syntetazy OTA mierzona w czasie przy pomocy odwrotnej transkryptazy...
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Support Vector Machine Applied to Road Traffic Event Classification
PublikacjaThe aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application...
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Modeling in Machine Design
Kursy OnlineThe course is meant to show the students how to build calculation models in machine design
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Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
PublikacjaDeep eutectic solvents (DES) represent a promising class of green solvents, offering particular utility in the extraction and development of new formulations of natural compounds such as ferulic acid (FA). The experimental phase of the study undertook a systematic investigation of the solubility of FA in DES, comprising choline chloride or betaine as hydrogen bond acceptors and six different polyols as hydrogen bond donors....
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Safe Operation of Underground Mining Vehicles Based on Cyclic Fatigue Monitoring of Powertrains
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Acoustic Emission Monitoring of Structural Elements of a Ship for Detection of Fatigue and Corrosion Damages
PublikacjaUszkodzenia korozyjne i pęknięcia zmęczeniowe są głównymi przyczynami defektów strukturalnych we wszystkich środkach transportu takich jak statki, cysterny drogowe i kolejowe. Oba typy degradacji tzn. degradacja materiału i konstrukcji są przedmiotem badań przeprowadzanych w projekcie badawczym VII Programu Ramowego Unii Europejskiej o nazwie ''Monitorowanie efektywnych kosztów korozji i zmęczenia w środkach transportu'' (akronim...
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Structural Health Monitoring of Overhead Power Transmission Lines
PublikacjaStructural Health Monitoring (SHM) is a novel and continuously developing branch of science and technology that draws attention of scientists all over the world. It creates opportunities to detect, localize and identify structural damage of various types such as: line breakage, permissible sag, bolt loosening, fatigue cracking or insulator contamination. On the other hand the methods used to estimate the remaining operational...
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Comparison of different one-parameter damage laws and local stress-strain approaches in multiaxial fatigue life assessment of notched components
PublikacjaThis paper aims to compare the predictive capabilities of different one-parameter damage laws and local stress-strain approaches to assess the fatigue lifetime in notched components subjected to proportional bending-torsion loading. The tested fatigue damage parameters are defined using well-known stress-based, strain-based, SWT-based and energy-based relationships. Multiaxial cyclic plasticity at the notch-controlled process zone...
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Andrzej Chybicki dr inż.
OsobyZ wykształcenia informatyk, absolwent Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej, doktor nauk technicznych w dziedzinie informatyka specjalizujący się w przetwarzaniau danych przestrzennych w rozproszonych systemach informatycznych. Ukierunkowany na wykorzystywanie osiągnięć i wiedzy zakresu prowadzonych badań w przemyśle. Współpracował z szeregiem podmiotów przemysłu informatycznego, geodezyjnego...
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The conception of energetic investigations of the multisymptom fatigue of the simple mechanical systems' constructional materials
PublikacjaThe article presents the basic assumptions of the research project aimed, as the main scientific purpose, an identification of the slow-changeable energy processes surrounding the high-cycle fatigue of constructional materials within the plain mechanical system, especially the marine one, for diagnostic purposes. There is foreseen an application of alternative diagnostic methods based on energetic observations of the multi-symptom,...
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Examining Influence of Distance to Microphone on Accuracy of Speech Recognition
PublikacjaThe problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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Resource constrained neural network training
PublikacjaModern 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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Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning
PublikacjaCervical cancer (CC) is one of the most common female cancers worldwide. It remains a significant global health challenge, particularly affecting women in diverse regions. The pivotal role of human papillomavirus (HPV) infection in cervical carcinogenesis underscores the critical importance of diagnostic strategies targeting both HPV infection and cervical...
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AN ENERGY APPROACH TO THE FATIGUE LIFE OF SHIP PROPULSION SYSTEMS
PublikacjaThe conducted research investigations aimed to carry out an identification of the constructional materials fatigue state of the ship propulsions’ rotational mechanical units for diagnostic purposes. The fatigue cracks of the elements transmitting mechanical energy streams from the propulsion engines to the ship propellers or to the generators of the ship’s electric power station stand for a primary reason for the secondary, usually...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublikacjaIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Towards solving heterogeneous fleet vehicle routing problem with time windows and additional constraints: real use case study
PublikacjaIn advanced logistic systems, there is a need for a comprehensive optimization of the transport of goods, which would reduce costs. During past decades, several theoretical and practical approaches to solve vehicle routing problems (VRP) were proposed. The problem of optimal fleet management is often transformed to discrete optimization problem that relies on determining the most economical transport routes for a number of vehicles...
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Streaming Real-time Data in Distributed Dispatcher and Teleinformation Systems for Visualization of Multimedia Data of the Border Guard
PublikacjaSurveillance of the sea borders is a very important task for the Border Guard. Monitoring of country maritime border is an important task of the Border Guard. This task can be facilitated with the use of the technology enabling gathering information from distributed sources and its supervision and visualization. This task can be accomplished using a technology that allows to collect information from distributed sensors of different...
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TIME SERIES MODELING (PG_00063724)
Kursy OnlineEffectively uses in-depth knowledge of economic time series analysis methods, applying the results of analyzes to formulate forecasts. Subject contents: 1. Classical time series analysis (trend, cyclical fluctuations) 2. Exponential smoothing models 3. Holt and Winters model 4. Stochastic processes and time series 5. Characteristics of stochastic processes 6. Process spectrum autocorrelation functions 7. Study of the stationarity...
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Multiclass AdaBoost Classifier Parameter Adaptation for Pattern Recognition
PublikacjaThe article presents the problem of parameter value selection of the multiclass ``one against all'' approach of an AdaBoost algorithm in tasks of object recognition based on two-dimensional graphical images. AdaBoost classifier with Haar features is still used in mobile devices due to the processing speed in contrast to other methods like deep learning or SVM but its main drawback is the need to assembly the results of binary...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublikacjaPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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Uncertainty in emotion recognition
PublikacjaPurpose–The purpose of this paper is to explore uncertainty inherent in emotion recognition technologiesand the consequences resulting from that phenomenon.Design/methodology/approach–The paper is a general overview of the concept; however, it is basedon a meta-analysis of multiple experimental and observational studies performed over the past couple of years.Findings–The mainfinding of the paper might be summarized as follows:...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublikacjaThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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Agnieszka Landowska dr hab. inż.
OsobyUkończyła studia na dwóch kierunkach: Finanse i bankowość na Uniwersytecie Gdańskim oraz Informatyka na WETI Politechniki Gdańskiej. Od 2000 roku jest związana z Politechniką Gdańską. W 2006 roku uzyskała stopień doktora w dziedzinie nauk technicznych, a w roku 2019 stopień doktora habilitowanego. Aktualnie jej praca naukowa dotyczy zagadnień interakcji człowiek-komputer oraz informatyki afektywnej (ang. affective computing), która...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions
PublikacjaAbstract— Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who...
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Machine Learning and data mining tools applied for databases of low number of records
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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