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Search results for: ELECTROENCEPHALOGRAPHY (EEG), ARTIFACT REMOVAL, AVERAGE EVENT DURATION, BLIND ASSESSMENT, MISSING GROUND TRUTH, RATING BY DETECTION, REAL DATA
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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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MICROSEISMIC EVENT DETECTION USING DIFFERENT ALGORITHMS ON REAL DATA FROM PATCH ARRAY GEOPHONE GRID FROM EASTERN POMERANIA FRACTURING JOB
PublicationThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing process. Hydraulic fracturing is a method of reservoir stimulation used especially for unconventional gas recovery. A matrix of several thousand geophones is placed on the surface of earth to record every little tremor of ground induced by fracturing process. Afterwards, the signal is analysed and the place of tremor occurrence...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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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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Assessment of hearing in coma patients employing auditory brainstem response, electroencephalography, and eye-gaze-tracking
PublicationThe results of the study conducted by Tagliaferri et al. in 12 European countries indicate that the ratio of registered brain injury cases in Europe amounts to 150-300 per 100 000 people, with the European mean value of 235 cases per 100 000 people. The project presented in the paper assumes development of a combined metric of patients’ state remaining in coma by intelligent fusion of GCS (subjective Glasgow Coma Scale or its derivatives)...
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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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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks
PublicationA method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved...
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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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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 Framework for Visual Event Detection in Parking Lot Area
PublicationThe paper presents the framework for automatic detection of various events occurring in a parking lot basing on multiple camera video analysis. The framework is massively distributed, both in the logical and physical sense. It consists of several entities called node stations that use XMPP protocol for internal communication and SRTP protocol with Jingle extension for video streaming. Recognized events include detecting parking...
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Comparison of Traffic Flow Models with Real Traffic Data Based on a Quantitative Assessment
PublicationThe fundamental relationship of traffic flow and bivariate relations between speed and flow, speed and density, and flow and density are of great importance in transportation engineering. Fundamental relationship models may be applied to assess and forecast traffic conditions at uninterrupted traffic flow facilities. The objective of the article was to analyze and compare existing models of the fundamental relationship. To that...
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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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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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Magdalena Szuflita-Żurawska
PeopleHead of the Scientific and Technical Information Services at the Gdansk University of Technology Library and the Leader of the Open Science Competence Center. She is also a Plenipotentiary of the Rector of the Gdańsk University of Technology for open science. She is a PhD Candidate. Her main areas of research and interests include research productivity, motivation, management of HEs, Open Access, Open Research Data, information...
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Histogram of Gradients with Cell Average Intensity for Human Detection
PublicationThe modification of the descriptor in human detector using Histogram of Oriented Gradients and support vector machine is presented. The proposed modification requires inserting the average cell intensitiesresulting with the increase of the length of the descriptor from 3780 to 4200 values, but it is easy to compute and instantly gives 14-26% of miss rate improvement at 10^-4 False Positives Per Window (FPPW). The modification...
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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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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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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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Histogram of Oriented Gradients with Cell Average Brightness for Human Detection
PublicationA modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The...
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Methods of trend removal in electrochemical noise data – overview
PublicationIn this paper we shall review popular methods of trend removal from electrochemical noise time records. The basic principles of operation of the six most popular methods are explained. The proposed methods are: high - pass filtering, Moving Average Removal, polynomial detrending, wavelet detrending, Empirical Mode Decomposition and Variational Mode Decomposition. Estimation of trend removal quality...
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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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Real-Time Bleeding Detection in Gastrointestinal Tract Endoscopic Examinations Video
PublicationThe article presents a novel approach to medical video data analysis and recognition of bleedings. Emphasis has been put on adapting pre-existing algorithms dedicated to the detection of bleedings for real-time usage in a medical doctor’s office during an endoscopic examination. A real-time system for analyzing endoscopic videos has been designed according to the most significant requirements of medical doctors. The main goal of...
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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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Detection and time/frequency analysis of electric fields in the ground
PublicationThis paper sets out to detect and characterize electric fields in the ground (such as stray current fields) using a tandem time/frequency method of signal analysis. Results were obtained from investigations performed in the presence of a generated electric field with controlled variable characteristics, and in the presence of an electric field generated by a tramline. The analysis of measurement registers was performed using Short‐Time...
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Toward Robust Pedestrian Detection With Data Augmentation
PublicationIn this article, the problem of creating a safe pedestrian detection model that can operate in the real world is tackled. While recent advances have led to significantly improved detection accuracy on various benchmarks, existing deep learning models are vulnerable to invisible to the human eye changes in the input image which raises concerns about its safety. A popular and simple technique for improving robustness is using data...
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Rating Prediction with Contextual Conditional Preferences
PublicationExploiting contextual information is considered a good solution to improve the quality of recommendations, aiming at suggesting more relevant items for a specific context. On the other hand, recommender systems research still strive for solving the cold-start problem, namely where not enough information about users and their ratings is available. In this paper we propose a new rating prediction algorithm to face the cold-start...
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Wave propagation in damage assessment of ground anchors
PublicationThe inspection possibilities of ground anchors are limited to destructive test such as pull-out test. Guided wave propagation gives an opportunity to develop an inspection system dedicated to determine the condition of inspected element without violation of their integrity. In this paper the experimental study on wave propagation in laboratory models of ground anchors are presented. Experiments were conducted for different bonding...
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Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations
PublicationAn evaluation of the sound event detection, classification and localization of hazardous acoustic events in the presence of background noise of different types and changing intensities is presented. The methods for separating foreground events from the acoustic background are introduced. The classifier, based on a Support Vector Machine algorithm, is described. The set of features and samples used for the training of the classifier...
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Change Detection in Signals 2023
e-Learning CoursesChange Detection in Signals - files for students.
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Artifact
Journals -
Specific detection of Alternaria alternata by PCR and real-time PCR
PublicationFungi of Alternaria genus are cosmopolitan organisms, which spores can be found in the air, soil, water, clothing and food. They commonly occur as saprotrophs on the plant remains, contributing to the decomposition of organic matter. Additionally, they are components of the normal human and animal skin flora. Alternaria spp. are also known human allergens, causing hay fever and allergic reactions that can lead to the development...
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Overhead wires detection by FPGA real-time image processing
PublicationThe paper presents design and hardware implementation of real-time image filtering for overhead wires detection divided on image processing and results presentation blocks. The image processing block was separated from the whole implementation, and its delay and hardware complexity was analysed. Also the maximum frequency of image processing of the proposed implementation was estimated.
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Real-time generator of AIS/ARPA/GPS data
PublicationThe paper presents a real-time generator of AIS/ARPA/GPS position data in the standardized NMEA 0183 text format. Position data are produced by a set of various types of ships simulated on the Polish part of the Baltic Sea and are generated on defined IP/UDP addresses and RS-232 ports. In the simulation an extensive set of input parameters is taken into account including the number of particular types of ships, their dimensions,...
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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High frequency impulse ground penetrating radar application in assessment of interlayer connections
PublicationGround Penetrating Radar (GPR) technique is commonly used in the nondestructive evaluation of pavement structures. In particular, this method is used to estimate thicknesses of pavement layers as well as it can be utilized in advanced studies of pavement structures. The device presented in this paper comprise the high frequency impulse antennas that allow for investigating the interlayer zones in terms of their electromagnetic...
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MATCHED FILTER APPROACH FOR MICROSEISMIC SIGNAL PROCESSING OF REAL DATA FROM EAST POMERANIA SHALE GAS
PublicationThe microseismic monitoring is a method of monitoring of fracture propagation during hydraulic fracturing (HF)process. An array of several hundred geophones is placed on the surface to record little ground tremors induced by fracturing process. Filtration and summation of signals from geophones is essential to identify and locate fracturing events from underground. Authors propose a method of matched filtering, that is usually...
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Color Processing for Color-Blind Individuals Using Smart Glasses
PublicationIn this paper we investigated image processing methods for color-blind individuals. In particular we experimentally verified color naming procedure, generation of maps with color perception differences for average observers and for dichromats, and two color transformation methods. In experiments 7 mobile devices were used: 3 smart glasses and 4 smartphones. User studies were performed with 38 average observers and 9 dichromats....
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Real-time PCR approach in dermatophyte detection and Trichophyton rubrum identification
PublicationDermatophytes are keratinophilic molds that infect human hair, nails and skin. Diagnosis of dermatophytosis is based on morphological, serological and biochemical features. However, identification is difficult and laborious due to similarities between microorganisms. Thus, there is considerable interest to develop mycological diagnostic procedures based on molecular biology methods. In this study, fast, two-step DNA extraction...
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Detection of Anomalies in the Operation of a Road Lighting System Based on Data from Smart Electricity Meters
PublicationSmart meters in road lighting systems create new opportunities for automatic diagnostics of undesirable phenomena such as lamp failures, schedule deviations, or energy theft from the power grid. Such a solution fits into the smart cities concept, where an adaptive lighting system creates new challenges with respect to the monitoring function. This article presents research results indicating the practical feasibility of real‐time...
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Missing Verification of Source Data in Hypertension Research: The HYGIA PROJECT in Perspective
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Expectation-Maximization Model for Substitution of Missing Values Characterizing Greenness of Organic Solvents
PublicationOrganic solvents are ubiquitous in chemical laboratories and the Green Chemistry trend forces their detailed assessments in terms of greenness. Unfortunately, some of them are not fully characterized, especially in terms of toxicological endpoints that are time consuming and expensive to be determined. Missing values in the datasets are serious obstacles, as they prevent the full greenness characterization of chemicals. A featured...
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Methods of navigation in the mobile application supporting movement of the blind
PublicationThis paper presents conclusions from the last development phase of the “Voice Maps” project. Authors specify newly found available options for navigation in affordable system for the blind with all their related aspects. System uses dedicated geographical data, built-in smartphone GPS receivers and DGPS external device in order to assist blind users in their everyday travelling. Authors also discuss new methods to improve positioning...
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Acceleration of decision making in sound event recognition employing supercomputing cluster
PublicationParallel processing of audio data streams is introduced to shorten the decision making time in hazardous sound event recognition. A supercomputing cluster environment with a framework dedicated to processing multimedia data streams in real time is used. The sound event recognition algorithms employed are based on detecting foreground events, calculating their features in short time frames, and classifying the events with Support...
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“The Guardians of the Truth”: Journalists’ Resistance to the Algorithmization of Journalism
PublicationRegardless of the term used, be it “robot journalism,” “automated journalism,” “algorithmic journalism” or “machine-written journalism,” the process of automatic content creation and distribution is progressing in the newsrooms. Meanwhile, exercising control over the creation and distribution of news is considered a fundamental element of journalists’ professional identity. The article presents the results of research on the perception...
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Wearable system supporting navigation of the blind
PublicationImproving blind people comfort of life is a problem ofgreat importance. Fortunately, new technolgies provide us withadditional methods to improve everyday life of the blind and visuallyimpaired. The paper presents experimental system made byresearchers from Department of Geoinformatics of Gdansk Universityof Technology, which is capable of finding the route from theindicated source to chosen destination, using dedicated digital...
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Estimating the Average Speed of Public Transport Vehicles Based on Traffic Control System Data
PublicationIntelligent Transport Systems are a valuable source of traffic information, covering both private and public vehicles. The main problem, however, is that very few studies are conducted to determine the speed of buses, trams and trolleys in urban networks in relation to traffic conditions. The paper investigates how ITS systems data could be used to model the speed of Public Transport vehicles. This is now possible thanks to the...
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Nutrient removal in municipal wastewater treatment
e-Learning CoursesThis series of lectures and interactive teaching sessions will cover all the important aspects of nutrient removal in municipal wastewater treatment. There will be five sessions. The topics of the sessions are: 1) Nutrient removal – why, how and what has been achieved?; 2) Biological treatment processes and conventional nitrogen removal; 3) Shortcut nitrogen removal processes and climate implication of nitrogen removal; 4) Biological...
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Crack Detection in Metallic Surfaces Based on Dumbbell-Shaped Defected Ground Structures in Microstrip Technology
PublicationIn this paper, a novel crack detection sensor using a microstrip loaded with a Dumbbell-Shaped Defected Ground Structure (DS-DGS) is proposed. The sensing element is etched in the ground plane of a microstrip line and it is easy to fabricate. The electromagnetic (EM) field of the microstrip couples to the DS-DGS, thus demonstrating a bandstop behavior. It is shown that in the presence of a crack in a metallic surface underneath the...
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The method of detection of electromagnetic fields in ground
PublicationW prezentowanej metodzie, detekcja pola polega na pomiarach i analizie zmian rozkładu potencjału. Różnice potencjałów są mierzone jako napięcie pomiędzy elektrodami umieszczonymi w różnych pozycjach na powierzchni ziemi. Analiza tych napięć przy pomocy krótkoczasowej transformaty Fouriera STFT umożliwia wyznaczenie zmian spektralnej gęstości mocy sygnału w funkcji czasu. Ten rodzaj łącznej analizy czasowo-częstotliwościowej daje...
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3D Object Shape Reconstruction from Underwater Multibeam Data and Over Ground Lidar Scanning
PublicationThe technologies of sonar and laser scanning are an efficient and widely used source of spatial information with regards to underwater and over ground environment respectively. The measurement data are usually available in the form of groups of separate points located irregularly in three-dimensional space, known as point clouds. This data model has known disadvantages, therefore in many applications a different form of representation,...