Search
Filters
total: 1419
filtered: 1104
-
Catalog
Chosen catalog filters
displaying 1000 best results Help
Search results for: SINGING EXPRESSION CLASSIFICATION
-
Application of an Electronic Nose Instrument to Fast Classification of Polish Honey Types
PublicationThe paper presents practical utilization of an electronic nose prototype, based on the FIGARO semiconductor sensors, in fast classification of Polish honey types—acacia flower, linden flower, rape, buckwheat and honeydew ones. A set of thermostating modules of the prototype provided gradient temperature characteristics of barbotage-prepared gas mixtures and stable measurement conditions. Three chemometric data analysis methods...
-
Production of Toxoplasma gondii MAG1 recombinant antigen in Leishmania tarentolae expression system
PublicationThe results of the work associated with the production of the Toxoplasma gondii matrix antigen 1 (MAG1) in the eukaryotic expression system of Leishmania tarentolae are shown.
-
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...
-
CLASSIFICATION OF RESTRAINTS IN THE OPTIMIZATION PROBLEM OF A COLD-FORMED PROFILE
PublicationThis work describes the restraints in the optimization problem. This is an important and complicated issue because it requires taking into account a vast range of information related to the design and production. In order to describe the relations of a specific optimization problem, it is essential to adopt appropriate criteria and to collect information on all kinds of restraints, i.e. boundary conditions. The following paper...
-
Potential and Use of the Googlenet Ann for the Purposes of Inland Water Ships Classification
PublicationThis article presents an analysis of the possibilities of using the pre-degraded GoogLeNet artificial neural network to classify inland vessels. Inland water authorities monitor the intensity of the vessels via CCTV. Such classification seems to be an improvement in their statutory tasks. The automatic classification of the inland vessels from video recording is a one of the main objectives of the Automatic Ship Recognition and...
-
Comparative Analysis of Text Representation Methods Using Classification
PublicationIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
-
Classification of high-voltage varistors into groups of differentiated quality
PublicationThe research was aimed on defining a factor of quality for high-voltage varistors using Non-Destructive Testing (NDT) techniques, which could be applied during the production testing. The newly proposed parameter Q determined on the basis of the lowest resonant frequency fr measured within the preselected frequency range was taken into account. The parameter Q was defined for ZnO structures after firing, without metallized contacts....
-
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...
-
Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
-
Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
-
Identification, Assessment and Automated Classification of Requirements Engineering Techniques
PublicationSelection of suitable techniques to be used in requirements engineering or business analysis activities is not easy, especially considering the large number of new proposals that emerged in recent years. This paper provides a summary of techniques recommended by major sources recognized by the industry. A universal attribute structure for the description of techniques is proposed and used to describe 33 techniques most frequently...
-
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....
-
Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
-
A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
-
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...
-
Expression of cyclin D1 after treatment with doxorubicin in the HL-60 cell line
PublicationIncreased levels of cyclin D1 and amplification of CCND1 gene occur in many types of cancers. We have followed the expression of cyclin D1 after treatment with doxorubicin with reference to cell death and other possible therapeutic implications. The effect of the treatment on the cell cycle, survival, intracellular level (flow cytometry), and intracellular localization of cyclin D1 (fluorescence microscopy) and expression of...
-
Towards Cancer Patients Classification Using Liquid Biopsy
PublicationLiquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier...
-
Classification methods and criteria
PublicationKlasyfikacja akustyczna dna morskiego jest najnowszą metodologią zaprojektowaną w celu zdalnego wykrywania rozmaitych charakterystyk dna morskiego z informacji zawartych w echch od dna akustycznych impulsów transmitowanych z różnego typu sonarów. Poza szególnymi chrakterystykami sprzętowymi każdego systemu ASC, istotą każdej metody jest klasyfikacja modułu, który wyciąga serie cech z echa sygnału i przetwarza je aby posortować...
-
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...
-
A New Expression for the 3-D Dyadic FDTD-Compatible Green's Function Based on Multidimensional Z-Transform
PublicationIn this letter, a new analytic expression for the time-domain discrete Green's function (DGF) is derived for the 3-D finite-difference time-domain (FDTD) grid. The derivation employs the multidimensional Z-transform and the impulse response of the discretized scalar wave equation (i.e., scalar DGF). The derived DGF expression involves elementary functions only and requires the implementation of a single function in the multiple-precision...
-
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...
-
The external walls of a passive building: A classification anddescription of their thermal and optical properties
PublicationThis paper attempts a new classification of insulating materials from the perspective of their utility in thepro-ecological passive construction industry. The main criterion is the conductivity of thermal and solarenergy. Based on their ability to conduct or block fluxes of thermal and solar energy, six types of insulatingwalls are proposed. On the basis of this criterion there are traditional dividing walls (typical walls, wallinsulating...
-
Transcriptomic responses to wounding: meta-analysis of gene expression microarray data
PublicationBackground A vast amount of microarray data on transcriptomic response to injury has been collected so far. We designed the analysis in order to identify the genes displaying significant changes in expression after wounding in different organisms and tissues. This meta-analysis is the first study to compare gene expression profiles in response to wounding in as different tissues as heart, liver, skin, bones, and spinal cord, and...
-
Analyzing the Impact of Simulated Multispectral Images on Water Classification Accuracy by Means of Spectral Characteristics
PublicationRemote sensing is widely applied in examining the parameters of the state and quality of water. Spectral characteristics of water are strictly connected with the dispersion of electromagnetic radiation by suspended matter and the absorp-tion of radiation by water and chlorophyll a and b.Multispectral sensor ALI has bands within the ranges of electromagnetic radia-tion: blue and infrared, absent in sensors such as Landsat, SPOT,...
-
Novel method of expression and purification of hirudin based on pBAD TOPO, pTYB12 vectors and gene synthesis
PublicationW pracy przedstawiono nową, szybką i tanią metodę otrzymywania, ekspresji i oczyszczania białka hirudyny naturalnie izolowanego z ślinianek pijawki lekarskiej. Hirudyna pełni funkcje bezpośredniego inhibitora trombiny, głównego białka biorącego udział w tworzeniu skrzepów krwi. Właściwości te wykorzystywane są od wielu lat w klinice. Opracowana metoda pozwoliła uzyskać 17 mg/l hodowli E. coli białka o wysokiej czystości i aktywności...
-
Novel thermostable ssDNA-binding proteins from Thermus thermophilus and T. aquaticus-expression and purification
PublicationSklonowano w system ekspresyjny pET-30LIC Escherichia coli gen kodujący białka SSB-podobne Thermus thermophilus i T. aquaticus. Oczyszczono do homogenności białka SSB-podobne, a uzyskane preparaty umożliwiają wykonanie badań strukturalnych w/w białek.
-
Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublicationAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
-
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...
-
Methodology for Text Classification using Manually Created Corpora-based Sentiment Dictionary
PublicationThis paper presents the methodology of Textual Content Classification, which is based on a combination of algorithms: preliminary formation of a contextual framework for the texts in particular problem area; manual creation of the Hierarchical Sentiment Dictionary (HSD) on the basis of a topically-oriented Corpus; tonality texts recognition via using HSD for analysing the documents as a collection of topically completed fragments...
-
Genome-Wide DNA Methylation and Gene Expression in Patients with Indolent Systemic Mastocytosis
PublicationMastocytosis is a clinically heterogenous, usually acquired disease of the mast cells with a survival time that depends on the time of onset. It ranges from skin-limited to systemic disease, including indolent and more aggressive variants. The presence of the oncogenic KIT p. D816V gene somatic mutation is a crucial element in the pathogenesis. However, further epigenetic regulation may also affect the expression of genes that...
-
Mathematical analysis of a generalised p53-Mdm2 protein gene expression model
PublicationWe propose the generalisation of the p53-Mdm2 protein gene expression model introduced by Monk (2003). We investigate the stability of a unique positive steady state and formulate conditions which guarantee the occurrence of the Hopf bifurcation. We show that oscillatory behaviour can be caused not only by time lag in protein transcription process, but also can be present in the model without time delay. Moreover, we investigate...
-
Support Vector Machine Applied to Road Traffic Event Classification
PublicationThe 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...
-
Development of an AI-based audiogram classification method for patient referral
PublicationHearing loss is one of the most significant sensory disabilities. It can have various negative effects on a person's quality of life, ranging from impeded school and academic performance to total social isolation in severe cases. It is therefore vital that early symptoms of hearing loss are diagnosed quickly and accurately. Audiology tests are commonly performed with the use of tonal audiometry, which measures a patient's hearing...
-
Prokaryotic expression systems
Publication -
Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublicationThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
-
Improving the Accuracy in Sentiment Classification in the Light of Modelling the Latent Semantic Relations
PublicationThe research presents the methodology of improving the accuracy in sentiment classification in the light of modelling the latent semantic relations (LSR). The objective of this methodology is to find ways of eliminating the limitations of the discriminant and probabilistic methods for LSR revealing and customizing the sentiment classification process (SCP) to the more accurate recognition of text tonality. This objective was achieved...
-
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...
-
An Overview of the Development of a Real-Time System for Endoscopic Video Classification
PublicationThe article presents the results of improving endoscopic image classification algorithms in an effort towards applying them in a real-time diagnosis supporting system. Methods for the detection and removal of personal data are presented and discussed. The currently developed recognition algorithms have been improved in terms of accuracy and performance to make them suitable for a real-life implementation. Their test results are...
-
Traffic Noise Analysis Applied to Automatic Vehicle Counting and Classification
PublicationProblems related to determining traffic noise characteristics are discussed in the context of automatic dynamic noise analysis based on noise level measurements and traffic prediction models. The obtained analytical results provide the second goal of the study, namely automatic vehicle counting and classification. Several traffic prediction models are presented and compared to the results of in-situ noise level measurements. Synchronized...
-
Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublicationThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
-
Post-Effort Changes in Autophagy- and Inflammation-Related Gene Expression in White Blood Cells of Healthy Young Men
PublicationAcute, strenuous physical exertion requiring high levels of energy production induces the production of reactive oxygen species and metabolic disturbances that can damage the mitochondria. Thus, selective autophagic elimination of defective mitochondria may improve resistance to oxidative stress and potentially to inflammation. The main goal of this study was to evaluate the impacts of intense effort on changes in the expression...
-
Classification of submandibular salivary stones based on ultrastructural studies
PublicationIntroduction: Sialolithiasis remains a clinical problem with unclear etiopathogenesis, lack of prevention methods, and only surgical treatment. Materials and methods: An ultrastructure examination of submandibular sialoliths obtained from patients with chronic sialolithiasis was conducted using a scanning electron microscope and X‐ray photoelectron spectroscopy. Results: Based on the results, we divided sialoliths into three types:...
-
Influence of Escherichia coli on Expression of Selected Human Drug Addiction Genes
PublicationThe impact of enteric microflora on the expression of genes associated with cocaine and amphetamine addiction was described. Human genome-wide experiments on RNA transcripts expressed in response to three selected Escherichia coli strains allowed for significant alteration (p > 0.05) of the linear regression model between HT-29 RNA transcripts associated with the KEGG pathway:hsa05030:Cocaine addiction after 3 h stimulation with...
-
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...
-
Classification of submandibular salivary stones based on ultrastructural studies
PublicationIntroduction: Sialolithiasis remains a clinical problem with unclear etiopathogenesis, lack of prevention methods, and only surgical treatment. Materials and methods: An ultrastructure examination of submandibular sialoliths obtained from patients with chronic sialolithiasis was conducted using a scanning electron microscope and X-ray photoelectron...
-
Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
-
Human UDP-Glucuronosyltransferases: Effects of altered expression in breast and pancreatic cancer cell lines.
PublicationIncreased aerobic glycolysis and de novo lipid biosynthesis are common characteristics of invasive cancers. UDP-glucuronosyltransferases (UGTs) are phase II drug metabolizing enzymes that in normal cells possess the ability to glucuronidate these lipids and speed their excretion; however, de-regulation of these enzymes in cancer cells can lead to an accumulation of bioactive lipids, which further fuels cancer progression. We hypothesize...
-
Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
-
INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
-
On the Role of Polarimetric Decomposition and Speckle Filtering Methods for C-Band SAR Wetland Classification Purposes
PublicationPrevious wetlands studies have thoroughly verified the usefulness of data from synthetic aperture radar (SAR) sensors in various acquisition modes. However, the effect of the processing parameters in wetland classification remains poorly explored. In this study, we investigated the influence of speckle filters and decomposition methods with different combinations of filter and decomposition windows sizes on classification accuracy....