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Search results for: eeg micro events
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Discrete analysis of micro-structural events in granular shear zones
PublicationW artykule pokazano rozwój różnych zjawisk mikrostrukturalnych na poziomie ziarna podczas parcia pasywnego piasku na sztywną ściankę przemieszczającą się poziomo. Obliczenia wykonano stosując metodę DEM. Wyniki na poziomie globalnym porównano z wynikami MES. Szczególna uwagę zwrócono na rozwój łańcuchów sił miedzy ziarnami.
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DEM analysis of micro-structural events within granular shear zones under passive earth pressure conditions
PublicationW artykule omówiono wyniki obliczeń numerycznych dla pasku dla stanu pasywnego sztywnej ścianki podczas jej translacji stosując metodę elementów dyskretnych. Analizowano głównie zjawiska mikrostrukturalne w strefach ścinania podczas translacji sztywnej ścianki. Szczególna uwagę zwrócono na pojawienie się wirów w materiale granulowanym.
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Corrosion Inhibition of Aluminium Alloy AA6063-T5 by Vanadates: Local Surface Chemical Events Elucidated by Confocal Raman Micro-Spectroscopy
PublicationChemical interactions between aqueous vanadium species and aluminium alloy AA6063-T5 were investigated in vanadate-containing NaCl solutions. Confocal Raman and X-ray photoelectron spectroscopy experiments were utilised to gain insight into the mechanism of corrosion inhibition by vanadates. A greenish-grey coloured surface layer, consisting of V+4 and V+5 polymerized species, was seen to form on the alloy surface, especially on...
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Labeler-hot Detection of EEG Epileptic Transients
PublicationPreventing early progression of epilepsy and sothe severity of seizures requires effective diagnosis. Epileptictransients indicate the ability to develop seizures but humansoverlook such brief events in an electroencephalogram (EEG)what compromises patient treatment. Traditionally, trainingof the EEG event detection algorithms has relied on groundtruth labels, obtained from the consensus...
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Invasive electrophysiological patient recordings from the human brain during memory tasks with pupilometry (MC_004)
Open Research DataData comprise intracranial EEG (iEEG) brain activity, including electrocorticography (ECoG) signals, recorded from over 100 electrodes implanted in one patient throughout various brain regions. These iEEG signals were recorded in epilepsy patients undergoing invasive monitoring and localization of seizures when they were performing a battery of four...
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Intracranial electrophysiological recordings from the human brain during memory tasks with pupillometry
PublicationData comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N=10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task...
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A study on microcrack monitoring in concrete: discrete element method simulations of acoustic emission for non-destructive diagnostics
PublicationThe research is focused on the monitoring of fracture evolution in concrete beams under three-point bending using the acoustic emission technique and the discrete element method. The main objective of the study was to numerically and experimentally investigate the mechanism behind the generation of elastic waves during acoustic emission events and their interaction with micro- and macro-cracking in concrete beams under monotonic...
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POSSIBILITY OF ASSESSMENT OF OPERATION OF SLIDING BEARINGS IN PISTON-CRANK MECHANISMS OF DIESEL ENGINES WITH REGARD TO LOAD AND TIME OF CORRECT WORK OF THE BEARINGS BY APPLYING ACOUSTIC EMISSION AS A DIAGNOSTIC SIGNAL
PublicationAbstract: The paper presents a possibility of determining (assessing) operation of sliding bearings with multilayer bushings in crank-piston mechanisms of diesel engines. Properties of load and wear, particularly fatigue and abrasive, are characterized in general. Acoustic emission as a diagnostic signal was proved to be useful for detection of the wear of sliding and barrier layers. Results of measurements of acoustic emission...
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Abilities, Motivations, and Opportunities of Furloughed Employees in the Context of Covid-19: Preliminary Evidence From the UK
PublicationThe Covid-19 global pandemic is a crisis like no other, forcing governments to implement prolonged national lockdowns in an effort to limit the spread of the disease. As organizations aim to adapt and remain operational, employers can suspend or reduce work activity for events related to Covid-19 and claim government support to subsidize employee wages. In this way, some employees are placed on furlough (i.e., temporary unemployment)...
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Micro- and nanodosimetry
e-Learning CoursesMicro- and nanodosimetry (Mikro- i nanodozymetria) dla studentów studiów II stopnia WFTIMS
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Balance recognition on the basis of EEG measurement.
PublicationAlthough electroencephalography (EEG) is not typically used for verifying the sense of balance, it can be used for analysing cortical signals responsible for this phenomenon. Simple balance tasks can be proposed as a good indicator of whether the sense of balance is acting more or less actively. This article presents preliminary results for the potential of using EEG to balance sensing....
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Metody redukcji artefaktów w zapisie EEG.
PublicationPrzegląd i opis metod badania EEG jego uwarunkowań technicznych oraz problemy z tym związane. Dokonano przeglądu metod pozwalających na zredukowanie bądź eliminacje artefaktów w zapisie EEG.
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Comparison of the effectiveness of automatic EEG signal class separation algorithms
PublicationIn this paper, an algorithm for automatic brain activity class identification of EEG (electroencephalographic) signals is presented. EEG signals are gathered from seventeen subjects performing one of the three tasks: resting, watching a music video and playing a simple logic game. The methodology applied consists of several steps, namely: signal acquisition, signal processing utilizing z-score normalization, parametrization and...
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Tensor Decomposition for Imagined Speech Discrimination in EEG
PublicationMost of the researches in Electroencephalogram(EEG)-based Brain-Computer Interfaces (BCI) are focused on the use of motor imagery. As an attempt to improve the control of these interfaces, the use of language instead of movement has been recently explored, in the form of imagined speech. This work aims for the discrimination of imagined words in electroencephalogram signals. For this purpose, the analysis of multiple variables...
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Public valuation of social impacts. The comparison between mega and non-mega sporting events
PublicationThe main aim of this study is to assign value to intangible effects,including social impacts, which appear when organising sportingevents of various scales in the city of Gdansk located in northernPoland. A survey was conducted to determine the city residents’willingness-to-pay (WTP) using the contingent valuation method(CVM). The average WTP values, which ranged between PLN 6.04and PLN 46.34, show that the scale of the sporting...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublicationEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublicationThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublicationThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Brain-computer interaction based on EEG signal and gaze-tracking information = Analiza interackji mózg-komputer wykorzystująca sygnał EEg i informacje z systemu śledzenia punktu fiksacji wzroku
PublicationThe article presents an attempt to integrate EEG signal analysis with information about human visual activities, i.e. gaze fixation point. The results from gaze-tracking-based measurement were combined with the standard EEG analysis. A search for correlation between the brain activity and the region of the screen observed by the user was performed. The preliminary stage of the study consists in electrooculography (EOG) signal processing....
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Automatic Clustering of EEG-Based Data Associated with Brain Activity
PublicationThe aim of this paper is to present a system for automatic assigning electroencephalographic (EEG) signals to appropriate classes associated with brain activity. The EEG signals are acquired from a headset consisting of 14 electrodes placed on skull. Data gathered are first processed by the Independent Component Analysis algorithm to obtain estimates of signals generated by primary sources reflecting the activity of the brain....
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Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion
PublicationA rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion....
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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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Rating by detection: an artifact detection protocol for rating EEG quality with average event duration
PublicationQuantitative evaluation protocols are critical for the development of algorithms that remove artifacts from real EEG optimally. However, visually inspecting the real EEG to select the top-performing artifact removal pipeline is infeasible while hand-crafted EEG data allow assessing artifact removal configurations only in a simulated environment. This study proposes a novel, principled approach for quantitatively evaluating algorithmically...
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MICRO
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublicationMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Distributed representation of information on cyclic events
PublicationA representation of information on cyclic events has been proposed which is advantageous for computing environments where a distributed set of Receivers reacts to cyclic events generated by distributed sources. In such scenario no immanent central information repository exist on event timing or volume. Receivers are able to learn the event cycles without communicating with each other, merely on the basis of the fact that an event...
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CLINICAL EEG AND NEUROSCIENCE
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Comparison of Methods for Real and Imaginary Motion Classification from EEG Signals
PublicationA method for feature extraction and results of classification of EEG signals obtained from performed and imagined motion are presented. A set of 615 features was obtained to serve for the recognition of type and laterality of motion using 8 different classifications approaches. A comparison of achieved classifiers accuracy is presented in the paper, and then conclusions and discussion are provided. Among applied algorithms the...
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Transfer learning in imagined speech EEG-based BCIs
PublicationThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublicationRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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Tangible and intangible economic impact of hosting mega sporting events
PublicationDue to the fact that the impetus for the creation of this paper was inaccuracies in the results of research relating to the economic effects caused by the organisation of mega sporting events, an analysis of the impact of 1988-2008 mega sporting events on host economies was conducted. The research shows that in selected areas of the economy, sporting events can be identified, with occasional positive (SOG) and negative (WOG) economic...
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EVENTS VISUALIZATION POST IN A DISTRIBUTED TELEINFORMATION SYSTEM FOR THE BORDER GUARD
PublicationEvents Visualization Post is a part of the STRADAR project, which is dedicated to streaming real-time data in distributed dispatcher and teleinformation systems of the Border Guard. Events Visualization Post is a software designed for simultaneous visualization of data of different types. In the paper, the structure of the software is presented, the process of generation of tasks is described, and the visualization of audio, files,...
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IMPACT OF THE ORGANISATION OF MEGA SPORTING EVENTS ON SELECTED ELEMENTS OF THE TOURISM SECTOR
PublicationIntroduction. In the world-wide literature, there is no unanimity in the assessment of the impact of mega sporting events on the tourism sector. Therefore, the main purpose of this study was to quantify the impact of mega sporting events on changes in tourist inflow and the amount of expenditure incurred by visitors. Material and methods. In this study, an ex-post analysis of many different categories of mega sporting events was...
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Social benefits valuation of hosting non-mega sporting events
PublicationPurpose In the study, an attempt was made to estimate the social benefits resulting from three non-mega sporting events organized in Ergo Arena located on the border of two cities in Poland. By attributing a value to intangible social benefits, the intangible effect was determined and compared to the expenditure incurred in the construction of Ergo Arena Hall. Design/methodology/approach In order to value social intangible effects...
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The set of 22 sessions of 14-channel eeg signals recorded during watching pictures
Open Research DataThe data were collected in order to perform research on the possibility of controlling the content displayed on the monitor screen using human emotional states extracted from EEG signals. The dataset contains recordings of 14-channel EEG signals collected from 10 persons within 22 sessions, during which 45 different random photos taken from the ImageNet...
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Micro and Nanosystems
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IEEE MICRO
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Micro and Nanostructures
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A MEASUREMENT SYSTEM FOR MONITORING CARDIOVASCULAR EVENTS IN SYNCOPE PATIENTS
PublicationSyncope phenomena is an abrupt and transient loss of consciousness leading to interruption of awareness of one’s surroundings and falls with risk of injury. Syncope is often followed by complete and usually rapid spontaneous recovery. It is said that half of all individuals experience syncopal event at least once during their life. The condition can occur at any age and happens in people with and without other medical problems....
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IS SMALLER BETTER? THE VALUATION OF SOCIAL IMPACTS OF DIFFERENTLY SIZED SPORTING EVENTS. THE CASE OF GDAŃSK
PublicationIntroduction. There is a discourse in the international literature regarding the impact of large sporting events on the place where they are held. In the last few years, particular emphasis has been laid on intangible effects, including social impacts that may occur not only in the case of mega sporting events but also in smaller sporting events. Therefore, the main aim of this paper is to estimate the monetary value of intangible...
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Performance Characteristics of a Micro-Turbine
PublicationIn the paper a design of a multi-stage micro-turbine with partial admission of all the stages is described in detail and the results of particular experimental investigations and numerical calculations are shown, followed by conclusions. The co-generative micro-power plant with the HFE7100 as a working medium was designed and built for experimental investigations. The values of the main cycle parameters were as follows:heat output:...
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Wspomaganie komunikacji w procesie neurorehabilitacji z wykorzystaniem śledzenia wzroku i analizy sygnałów EEG
PublicationW pracy przedstawiono charakterystykę systemu do wspomagania komunikacji w procesie neurorehabilitacji osób w stanie ograniczonej świadomości. Przygotowana aplikacja komputerowa wykorzystuje metodę śledzenia wzroku wspomaganą analizą sygnału EEG. W pracy podano genezę powstania systemu, scharakteryzowano zaimplementowane ćwiczenia oraz pozostałe funkcjonalności, a także zamieszczono wyniki wstępnych badań dokonanych w kilku polskich...
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A method for counting people attending large public events
PublicationThe algorithm for people counting in crowded scenes, based on the idea of virtual gate which uses optical flow method is presented. The concept and practical application of the developed algorithm under real conditions is depicted. The aim of the work is to estimate the number of people passing through entrances of a large sport hall. The most challenging problem was the unpredicted behavior of people while entering the building....
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[EiF] Economic theory - micro
e-Learning Courses{mlang pl} Dyscyplina: Ekonomia i Finanse Zajęcia obowiązkowe dla doktorantów I i II roku Prowadzący: dr hab. Tomasz Brodzicki Liczba godzin: 30 h Forma zajęć: wykład {mlang} {mlang en} Discipline: Economics and Finance Obligatory course for 1st and 2nd year PhD students Academic teacher: dr hab. Tomasz Brodzicki Total hours of training: 30 teaching hours Course type: lecture {mlang}
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A multi-agent method for periodicity detection in distributed events
PublicationMulti-agent systems working in constantly changing environments may be challenged by instantaneous unavailability of their autonomous agents caused e.g. by limited computing resources. A new method of self-organization of distributed service components is proposed, suitable for multi-agent systems. This method relies on particular agents carrying out separate analyzes of their individual processing loads or other specific events....
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Objects classification based on their physical sizes for detection of events in camera images
PublicationIn the paper, a method of estimation of the physical sizes of the objects tracked in the video surveillance system, and a simple module for object classification based on the estimated physical sizes, are presented. The results of object classification are then used for automatic detection of various types of events in the camera image.
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New trends in development of micro heat exchangers for ORC's
PublicationIn the paper, new trends in development of micro heat exchangers for CHP are presented. Main attention is concentrated on the question, how channels size and thermal development lenght affect the heat transfer. New types of micro heat exchangers developed at the Institute of Fluid-Flow Machinery PAS and the methoda of their design are presented. The new experimental testing methods of the micro-channel heat exchangers, new algorithms...