Search results for: SPIKE PROTEIN, SARS-COV-2, T-SNE ALGORITHM, CLASSIFICATION
-
Mask Detection and Classification in Thermal Face Images
PublicationFace masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify...
-
Assessing the Risk in Urban Public Transport for Epidemiologic Factors
PublicationPandemics have presented new challenges for public transport organisers and operators. New diseases (e.g., influenza H1N1, severe acute respiratory syndrome—SARS, as well as, more recently, SARS-CoV-2) increase the need for new protection measures to prevent epidemic outbreaks in public transport infrastructure. The authors’ goal is to present a set of actions in the area of public transport that are adjusted to different levels...
-
Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
-
Basic Hand Gestures Classification Based on Surface Electromyography
PublicationThis paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...
-
Network oscillations modulate interictal epileptiform spike rate during human memory
PublicationEleven patients being evaluated with intracranial electroencephalography for medically resistant temporal lobe epilepsy participated in a visual recognition memory task. Interictal epileptiform spikes were manually marked and their rate of occurrence compared between baseline and three 2 s periods spanning a 6 s viewing period. During successful, but not unsuccessful, encoding of the images there was a significant reduction in...
-
Materiały sorpcyjne wykorzystywane w maskach ochronnych
PublicationOd zarania dziejów ludzie starają się chronić przed chorobami zakaźnymi, stosując środki ochrony osobistej, do których należą maski ochronne. Z uwagi na obecnie panującą pandemię wirusa SARS-CoV-2, noszenie masek stało się normą w walce z koronawirusem. Jednak zagrożenia dla górnych dróg oddechowych nie stanowią wyłącznie wirusy, lecz również cząstki stałe zawieszone w powietrzu. Szczególnie w krajach wysoko uprzemysłowionych,...
-
Spike patterns and chaos in a map-based neuron model
PublicationThe work studies the well-known map-based model of neuronal dynamics introduced in 2007 by Courbage, Nekorkin and Vdovin, important due to various medical applications. We also review and extend some of the existing results concerning β-transformations and (expanding) Lorenz mappings. Then we apply them for deducing important properties of spike-trains generated by the CNV model and explain their implications for neuron behaviour....
-
Impact of optimization of ALS point cloud on classification
PublicationAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
-
Statistical evaluation of physical and index properties of Vistula Marshlands deltaic soft soils
PublicationThis paper provides statistical evaluation of physical and index parameters of the Vistula Marshlands deltaic soft soils using three datasets. Soft soils from the Vistula Marshlands are grouped into the four categories: (1) silty/sandy loams, (2) organic clays, (3) organic silts and (4) peats. Variability of basic and derivative physical properties as well as Atterberg's limits and plasticity index is studied. It is found that...
-
Clinical studies of detecting COVID-19 from exhaled breath with electronic nose
PublicationThe COVID‑19 pandemic has attracted numerous research studies because of its impact on society and the economy. The pandemic has led to progress in the development of diagnostic methods, utilizing the polymerase chain reaction (PCR) as the gold standard for coronavirus SARS‑CoV‑2 detection. Numerous tests can be used at home within 15 min or so but of with lower accuracy than PCR. There is still a need for point‑of‑care tests available...
-
Respiratory Rate Estimation Based on Detected Mask Area in Thermal Images
PublicationThe popularity of non-contact methods of measuring vital signs, particularly respiratory rate, has increased during the SARS-COV-2 pandemic. Breathing parameters can be estimated by analysis of temperature changes observed in thermal images of nostrils or mouth regions. However, wearing virus-protection face masks prevents direct detection of such face regions. In this work, we propose to use an automatic mask detection approach...
-
Characterization and Filtration Efficiency of Sustainable PLA Fibers Obtained via a Hybrid 3D-Printed/Electrospinning Technique
PublicationThe enormous world demand for personal protective equipment to face the current SARS-CoV-2 epidemic has revealed two main weaknesses. On one hand, centralized production led to an initial shortage of respirators; on the other hand, the world demand for single-use equipment has had a direct and inevitable effect on the environment. Polylactide (PLA) is a biodegradable, biocompatible, and renewable thermoplastic polyester, mainly...
-
Joanna Raczek dr inż.
PeopleEmployment 2003 -- 2019: Faculty of Applied Physics and Mathematics, Gdańsk University of Technology. 2019 - present: Faculty of Electronic, Informatics and Telecominications, Gdańsk University of Technology. Education May 2007: Doctor of Philosophy in Mathematics, University of Gdańsk. Doctoral dissertation: "Paired domination and doubly domination in graphs". Supervisor: dr hab. Jerzy Topp. 2000 -- 2004 Bachelor of Science...
-
Classification of Sea Going Vessels Properties Using SAR Satellite Images
PublicationThe aim of the project was to analyze the possibility of using machine learning and computer vision to identify (indicate the location) of all sea-going vessels located in the selected area of the open sea and to classify the main attributes of the vessel. The key elements of the project were to download data from the Sentinel-1 satellite [1], download data on the sea vessels [2], then automatically tag data and develop a detection...
-
Neural Networks, Support Vector Machine and Genetic Algorithms for Autonomous Underwater Robot Support
PublicationIn this paper, artificial neural networks, a classification technique called support vector machine and meta-heuristics genetic algorithm have been considered for development in autonomous underwater robots. Artificial neural networks have been used for seabed modelling as well as support vector machine has been applied for the obstacles classification to avoid some collision problems. Moreover, genetic algorithm has been applied...
-
Systematic approach to binary classification of images in video streams using shifting time windows
Publicationin the paper, after pointing out of realistic recordings and classifications of their frames, we propose a new shifting time window approach for improving binary classifications. We consider image classification in tewo steps. in the first one the well known binary classification algorithms are used for each image separately. In the second step the results of the previous step mare analysed in relatively short sequences of consecutive...
-
Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
-
Determination of viscosity changes of protein hydrolyzate solutions depending on shear rate
Open Research DataRheological characteristics of connective tissue protein solutions were made on the basis of viscosity measurement using a Brookfield viscometer using LV SC4 - 27 spindles and shear rate of 85 s-1 (Fig. 1). Solutions of protein hydrolysates with a concentration of 2% in 0.5M acetic acid were prepared.
-
Application of Support Vector Machine for Determination of Impact of Traffic-Induced Vibrations on Buildings
PublicationThe aim of the article is to present an algorithm of Support Vector Machine created to forecast the impact of traffic-induced vibrations on residential buildings. The method is designed to classify the object into one of two classes. The classification into the first class means that there is no impact of vibrations on the building, while classification to the second class indicates the possible influence and suggests the execution...
-
Accelerating Video Frames Classification With Metric Based Scene Segmentation
PublicationThis paper addresses the problem of the efficient classification of images in a video stream in cases, where all of the video has to be labeled. Realizing the similarity of consecutive frames, we introduce a set of simple metrics to measure that similarity. To use these observations for decreasing the number of necessary classifications, we propose a scene segmentation algorithm. Performed experiments have evaluated the acquired...
-
Water-mediated long-range interactions between the internal vibrations of remote proteins
PublicationIt is generally acknowledged that the mobility of protein atoms and the mobility of water molecules in the solvation layer are connected. In this article, we answer the question whether a similar interdependence exists between the motions of atoms of proteins separated by the hydration layers of variable thickness. The system consisted of a kinesin catalytic domain and a tubulin dimer. It was studied using molecular dynamics simulations....
-
The structurally similar TRFH domain of TRF1 and TRF2 dimers shows distinct behaviour towards TIN2
PublicationThe telomere repeat binding-factor 1 and 2 (TRF1 and TRF2) proteins of the shelterin complex bind to duplex telomeric DNA as homodimers, and the homodimerization is mediated by their TRFH (TRF-homology) domains. We performed molecular dynamic (MD) simulations of the dimer forms of TRF1TRFH and TRF2TRFH in the presence/absence of the TIN2TBM (TIN2, TRF-interacting nuclear protein 2, TBM, TRF-binding motif) peptide. The MD results...
-
Visually validated semi-automatic high-frequency oscillation detection aides the delineation of epileptogenic regions during intra-operative electrocorticography
PublicationOBJECTIVE: To test the utility of a novel semi-automated method for detecting, validating, and quantifying high-frequency oscillations (HFOs): ripples (80-200 Hz) and fast ripples (200-600 Hz) in intra-operative electrocorticography (ECoG) recordings. METHODS: Sixteen adult patients with temporal lobe epilepsy (TLE) had intra-operative ECoG recordings at the time of resection. The computer-annotated ECoG recordings were visually...
-
The computational complexity of the backbone coloring problem for planar graphs with connected backbones
PublicationIn the paper we study the computational complexity of the backbone coloring problem for planar graphs with connected backbones. For every possible value of integer parameters λ≥2 and k≥1 we show that the following problem: Instance: A simple planar graph GG, its connected spanning subgraph (backbone) HH. Question: Is there a λ-backbone coloring c of G with backbone H such that maxc(V(G))≤k? is either NP-complete or polynomially...
-
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...
-
Wykorzystanie klasyfikacji funkcjonalnej usług do efektywnego zarządzania zasobami chmurowymi
PublicationWykazano jak istotnym problemem jest zarzadzanie chmurą obliczeniową, w tym alokacja zasobów do wykonania usług (workloadów) zgłoszonych przez użytkownika. Przeanalizowano problem podziału usług wdrażanych w środowiskach chmurowych na klasy określające ich funkcjonalność. Zaproponowano oryginalną metodę alokacji workloadów wykorzystującą wprowadzoną klasyfikację funkcjonalną oraz identyfikację tych klas na podstawie wielkości generowanego...
-
Improving methods for detecting people in video recordings using shifting time-windows
PublicationWe propose a novel method for improving algorithms which detect the presence of people in video sequences. Our focus is on algorithms for applications which require reporting and analyzing all scenes with detected people in long recordings. Therefore one of the target qualities of the classification result is its stability, understood as a low number of invalid scene boundaries. Many existing methods process images in the recording...
-
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
-
Music Recommendation Based on Multidimensional Description and Similarity Measures . Rekomendacja muzyki na podstawie wielowymiarowego wektora cech i miar podobieństwa
PublicationThis study aims to create an algorithm for assessing the degree to which songs belong to genres defined a priori. Such an algorithm is not aimed at providing unambiguous classification-labelling of songs, but at producing a multidimensional description encompassing all of the defined genres. The algorithm utilized data derived from the most relevant examples belonging to a particular genre of music. For this condition to be met,...
-
Estimation of object size in the calibrated camera image = Estymacja rozmiaru obiektów w obrazach ze skalibrowanej kamery
PublicationIn the paper, a method of estimation of the physical sizes of the objects tracked by the camera is presented. First, the camera is calibrated, then the proposed algorithm is used to estimate the real width and height of the tracked moving objects. The results of size estimation are then used for classification of the moving objects. Two methods of camera calibration are compared, test results are presented and discussed. The proposed...
-
Monitoring of lysozyme thermal denaturation by volumetric measurements and nanoDSF technique in the presence of N-butylurea
PublicationThe results of thermal studies of denaturation of hen egg white lysozyme (HEWL) in water and an aqueous solution of N-butylurea (BU) are presented. High-precision densimetric measurements were used to characterize and analyze the changes of the specific volume, v, during temperature elevation. The temperature of the midpoint of protein denaturation was also determined by nanoDSF technique (differential scanning fluorimetry). The...
-
Camera angle invariant shape recognition in surveillance systems
PublicationA method for human action recognition in surveillance systems is described. Problems within this task are discussed and a solution based on 3D object models is proposed. The idea is shown and some of its limitations are talked over. Shape description methods are introduced along with their main features. Utilized parameterization algorithm is presented. Classification problem, restricted to bi-nary cases is discussed. Support vector...
-
The computational complexity of the backbone coloring problem for bounded-degree graphs with connected backbones
PublicationGiven a graph G, a spanning subgraph H of G and an integer λ>=2, a λ-backbone coloring of G with backbone H is a vertex coloring of G using colors 1, 2, ..., in which the color difference between vertices adjacent in H is greater than or equal to lambda. The backbone coloring problem is to find such a coloring with maximum color that does not exceed a given limit k. In this paper, we study the backbone coloring problem for bounded-degree...
-
Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations
PublicationEvaluation of 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 discerning between the events being in focus and 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...
-
Deep neural network architecture search using network morphism
PublicationThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
-
How Specific Can We Be with k-NN Classifier?
PublicationThis paper discusses the possibility of designing a two stage classifier for large-scale hierarchical and multilabel text classification task, that will be a compromise between two common approaches to this task. First of it is called big-bang, where there is only one classifier that aims to do all the job at once. Top-down approach is the second popular option, in which at each node of categories’ hierarchy, there is a flat classifier...
-
Flood Classification in a Natural Wetland for Early Spring Conditions Using Various Polarimetric SAR Methods
PublicationAbstract--- One of the major limitations of remote sensing flood detection is the presence of vegetation. Our study focuses on a flood classification using Radarsat-2 Quad-Pol data in a natural floodplain during leafless, dry vegetation (early spring) state. We conducted a supervised classification of a data set composed of nine polarimetric decompositions and Shannon entropy followed by the predictors' importance estimation to...
-
Investigation of Air Quality beside a Municipal Landfill: The Fate of Malodour Compounds as a Model VOC
PublicationThis paper presents the results of an investigation on ambient air odour quality in the vicinity of a municipal landfill. The investigations were carried out during the spring–winter and the spring seasons using two types of the electronic nose instrument. The field olfactometers were employed to determine the mean odour concentration, which was from 2.1 to 32.2 ou/m3 depending on the measurement site and season of the year. In...
-
Recent developments in automatic classification of musical instruments. W:[CD-ROM] Collected papers. First Pan-American/Iberian Meeting on Acoustics. 144 Meeting of the Acoustical Society of America. III Iberoamerican Cong- ress of Acoustics. 9o Mexican Congress of Acoustics. Cancun, Q. R. Mxico, 2-6 Dec. 2002. [B.m.:ASA]**2002 paper 2aMU4, 7 s. 6 rys. 1 tab. bibliogr. 21 poz. Automatyczne rozpoznawanie muzyki - przykłady eksperymentów.
PublicationW referacie dokonano przeglądu aktualnego stanu badań w dziedzinie automaty-cznego rozpoznawania muzyki. Przedstawiono też eksperymenty prowadzone aktu-alnie w Katedrze Dźwięku i Obrazu PG. Prace te dotyczyły rozpoznawania klasinstrumentów muzycznych i separacji duetów muzycznych. Pokazano przykładowewyniki i przedstawiono projekt prac do zrealizowania w przyszłych ekspery-mentach.
-
Contextual ontology for tonality assessment
Publicationclassification tasks. The discussion focuses on two important research hypotheses: (1) whether it is possible to construct such an ontology from a corpus of textual document, and (2) whether it is possible and beneficial to use inferencing from this ontology to support the process of sentiment classification. To support the first hypothesis we present a method of extraction of hierarchy of contexts from a set of textual documents...
-
A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms
PublicationThis paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.
-
Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublicationThe continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...
-
Layered background modeling for automatic detection of unattended objects in camera images
PublicationAn algorithm for automatic detection of unattended objects in video camera images is presented. First, background subtraction is performed, using an approach based on the codebook method. Results of the detection are then processed by assigning the background pixels to time slots, based on the codeword age. Using this data, moving objects detected during a chosen period may be extracted from the background model. The proposed approach...
-
Machine Learning in Multi-Agent Systems using Associative Arrays
PublicationIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
-
Agnieszka Potęga dr inż.
People -
Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
-
On Sample Rate Conversion Based on Variable Fractional Delay Filters
PublicationThe sample rate conversion algorithm based on variable fractional delay filters is often used if the resampling ratio cannot be expressed as the ratio of small integer numbers or if it is not constant. The main advantage of such solution is that it allows for arbitrary resampling ratios which can even be changed during the resampling process. In this paper a discussion on influence of different approaches to fractional filter...
-
Predictions of cervical cancer identification by photonic method combined with machine learning
PublicationCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
-
Rozpoznawanie oraz lokalizacja w obrazie przewodów linii wysokiego napięcia
PublicationW pracy przedstawiono opracowany algorytm rozpoznawania oraz lokalizacji przewodów linii wysokiego napięcia na podstawie obrazu horyzontalnego. Procedura detekcji przewodu została podzielona na trzy etapy. Pierwszy etap zawiera algorytm wykrywania krawędzi wykazujący największą czułość na krawędzie poziome, a jednocześnie brak czułości na krawędzie pionowe. Efektem jest znaczna redukcja liczby wykrytych krawędzi w porównaniu do...
-
ECG-based prediction of ventricular fibrillation by means of the PCA
PublicationA Sudden Cardiac Death (SCD) is a death resulting from cardiac failure with no significant symptoms earlier than one hour before occurrence. It is the cause of for approximately 400000 deaths per year in United States and millions of deaths worldwide. The proposed system, including two-stage algorithm and wearable diagnostic device allows for SCD risk estimation and continuous monitoring of high risk patients. A single channel...