Filters
total: 977
filtered: 777
-
Catalog
- Publications 777 available results
- Journals 4 available results
- People 46 available results
- Projects 3 available results
- Research Teams 1 available results
- Research Equipment 4 available results
- e-Learning Courses 15 available results
- Events 2 available results
- Open Research Data 125 available results
Chosen catalog filters
Search results for: KNN CLASSIFIER
-
Wikipedia Articles Representation with Matrix'u
PublicationIn the article we evaluate different text representation methods used for a task of Wikipedia articles categorization. We present the Matrix’u application used for creating computational datasets ofWikipedia articles. The representations have been evaluated with SVM classifiers used for reconstruction human made categories.
-
FEEDB: A multimodal database of facial expressions and emotions
PublicationIn this paper a first version of a multimodal FEEDB database of facial expressions and emotions is presented. The database contains labeled RGB-D recordings of people expressing a specific set of expressions that have been recorded using Microsoft Kinect sensor. Such a database can be used for classifier training and testing in face recognition as well as in recognition of facial expressions and human emotions. Also initial experiences...
-
Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
-
Problemy zarządzania międzykulturowego w przedsiębiorstwach z kapitałem zagranicznym
PublicationW artykule jest analizowana problematyka zarządzania międzykulturowego w przedsiębiorstwach z kapitałem zagranicznym jako filiach zagranicznych korporacji transnarodowych (KTN). Celem opracowania jest zidentyfikowanie potencjalnych obszarów problemów w zarządzaniu międzykulturowym występujących w filiach zagranicznych, ich przyczyn i skutków oraz mechanizmów wykorzystywanych przez KTN w kierunku przezwyciężania barier. W artykule...
-
Globalne i regionalne strategie internacjonalizacji przedsiębiorstw transnarodowych a bariery kulturowe
PublicationCelem referatu jest ukazanie związków między barierami kulturowymi a przepływami kapitałów prywatnych podejmowanych przez korporacje transnarodowe (KTN) ze szczególnym uwzględnieniem strategii internacjonalizacji globalnej i regionalnej. Na początku związek ten przedstawiono odwołując się do dorobku literatury z zakresu biznesu międzynarodowego. Scharakteryzowano skutki dystansu kulturowego dla przepływu kapitałów prywatnych KTN....
-
A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
-
Vehicle detector training with labels derived from background subtraction algorithms in video surveillance
PublicationVehicle detection in video from a miniature station- ary closed-circuit television (CCTV) camera is discussed in the paper. The camera provides one of components of the intelligent road sign developed in the project concerning the traffic control with the use of autonomous devices being developed. Modern Convolutional Neural Network (CNN) based detectors need big data input, usually demanding their manual labeling. In the presented...
-
APPLICATION OF ULTRAFAST GAS CHROMATOGRAPHY TO RECOGNIZE ODOR NUISANCE
PublicationPotentialities of ultrafast gas chromatography applied to periodical monitoring of odor nuisance originating from a municipal landfill have been examined. The results of investigation on classification of the atmospheric air samples collected in a vicinity of the landfill during winter and summer season have been presented. The investigation was performed using ultrafast gas chromatography of Fast/Flash GC type HERACLES II by Alpha...
-
Modelowanie matematyczne w procesie oczyszczania ścieków metodą osadu czynnego
PublicationModelowanie matematyczne w procesie oczyszczania ścieków metodą osadu czynnego dla możliwości zwiększenia efektywności w branży WOD-KAN
-
Diagnostic Accuracy of Liquid Biopsy in Endometrial Cancer
PublicationBackground: Liquid biopsy is a minimally invasive collection of a patient body fluid sample. In oncology, they offer several advantages compared to traditional tissue biopsies. However, the potential of this method in endometrial cancer (EC) remains poorly explored. We studied the utility of tumor educated platelets (TEPs) and circulating tumor DNA (ctDNA) for preoperative EC diagnosis, including histology determination. Methods:...
-
KEMR-Net: A Knowledge-Enhanced Mask Refinement Network for Chromosome Instance Segmentation
PublicationThis article proposes a mask refinement method for chromosome instance segmentation. The proposed method exploits the knowledge representation capability of Neural Knowledge DNA (NK-DNA) to capture the semantics of the chromosome’s shape, texture, and key points, and then it uses the captured knowledge to improve the accuracy and smoothness of the masks. We validate the method’s effectiveness on our latest high-resolution chromosome...
-
Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublicationIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...
-
Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublicationAbstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...
-
Dynamic Signature Vertical Partitioning Using Selected Population-Based Algorithms
PublicationThe dynamic signature is a biometric attribute used for identity verification. It contains information on dynamics of the signing process. There are many approaches to the dynamic signature verification, including the one based on signature partitioning. Partitions are the regions created on the basis of signals describing the dynamics of the signature. They contain information on the shape of the signature characteristic of a...
-
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...
-
Vehicle detector training with minimal supervision
PublicationRecently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...
-
Urządzenie do wytwarzania gazowych mieszanin wzorcowych z wykorzystaniem procesu barbotażu oraz permeacji
PublicationReference gas mixtures are classified to reference materials and are mainly used for quality monitoring and identification of impurities in atmospheric air. They can be also used for calibration of measuring devices. Nowadays, there is a need to develop a new techniques for the preparation of reference gas mixtures [1, 2]. In this paper the design and the operating principles of instrument based on the use of barbotage and permeation...
-
Bioterrorism — characteristics and possibilities of prevention
PublicationIn the paper bioterrorist threats have been presented. Historical background and possible methods of attacks have been described. The most dangerous pathogens and disease entities have been classified. Selected methods of detection and identification of biological weapon have been presented. The wireless system for threats monitoring — developed at Gdansk University of Technology — has been described.
-
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...
-
Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
-
Kultury organizacyjne przedsiębiorstw w biznesie międzynarodowym
PublicationW pracy analizowane są związki między kulturą organizacyjną przedsiębiorstw biznesu międzynarodowego a kulturami narodowymi. Głównym podmiotem biznesu międzynarodo-wego są korporacje transnarodowe (KTN), dlatego też przedstawione zależności odnoszą się przede wszystkim do tych podmiotów. Rozważania podzielono na trzy zasadnicze części. W pierwszej zawarto charakterystykę kultur narodowych, w drugiej opisano modele kultur orga-nizacyjnych....
-
Modelowanie przepływu pary przez okołodźwiękowe wieńce turbinowe z użyciem sztucznych sieci neuronoych
PublicationNiniejszy artykuł stanowi opis modelu przepływu pary przez okołodźwiękowe stopnie turbinowe, stworzonego w oparciu o sztuczne sieci neuronowe (SSN). Przedstawiony model neuronowy pozwala na wyznaczenie rozkładu wybranych parametrów w analizowanym przekroju kanału przepływowego turbiny dla rozpatrywanego zakresu wartości ciśnienia wlotowego.
-
Analytical Techniques Used in Monitoring of Atmospheric Air Pollutants
PublicationThe air pollution monitoring is one of the most pressing environmental problems today. The paper describes common air pollutants, their interaction and impact on the environment, and classifies the techniques and methods applied in air studies. Furthermore, the review characterizes the selected collection and sampling techniques used for gas sample analysis. Finally, the schematic diagrams of typical designs of systems applied...
-
Comparative analysis of various transformation techniques for voiceless consonants modeling
PublicationIn this paper, a comparison of various transformation techniques, namely Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Walsh Hadamard Transform (DWHT) are performed in the context of their application to voiceless consonant modeling. Speech features based on these transformation techniques are extracted. These features are mean and derivative values of cepstrum coefficients, derived from each transformation....
-
Scattering of Dirac particles from nonlocal separable potentials: The eigenchannel approach
PublicationZastosowano nowe sformułowanie metody kanałów własnych [R. Szmytkowski, Ann. Phys. (N.Y.) 311, 503 (2004)] w rozpraszaniu cząstek Diraca na nielokalnych potencjałach separowalnych.
-
Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublicationCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
-
Determination of Formaldehyde and Cyanide Ion in Human Nasal Discharge by Using Simple Spectrophotometric Methods
PublicationEnvironmental tobacco smoke (ETS) contains many toxic compounds which include substances classified as aldehydes (e.g. formaldehyde) and inorganic substances such as cyanide ions. The information on the determination of these compounds in water is available, but the monitoring data on the level of these substances in human body fluids are still lacking. In this work the procedure for determining cyanide ions and formaldehyde in...
-
Approximation of Fractional Order Dynamic Systems Using Elman, GRU and LSTM Neural Networks
PublicationIn the paper, authors explore the possibility of using the recurrent neural networks (RNN) - Elman, GRU and LSTM - for an approximation of the solution of the fractional-orders differential equations. The RNN network parameters are estimated via optimisation with the second order L-BFGS algorithm. It is done based on data from four systems: simple first and second fractional order LTI systems, a system of fractional-order point...
-
Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
-
Shape Optimisation of Kaplan Turbine Blades Using Genetic Algorithms
PublicationThis monograph is a comprehensive guide to a method of blade profile optimisation for Kaplan-type turbines. This method is based on modelling the interaction between rotor and stator blades. Additionally, the shape of the draft tube is investigated. The influence of the periodic boundary condition vs. full geometry is also discussed. Evolutionary algorithms (EA) are used as an optimisation method together with artificial neural...
-
ISSUES OF CLASSIFICATION FUNCTION CONTINUITY IN ENDOSCOPIC VIDEO CLASSIFICATION
PublicationIn the article a new way of analyzing the properties of feature vector functions (FVF) and classiers of images in a video stream is proposed. The general idea is based on focusing of the perceived continuity of the FVF and classier functions. Issues related to creating an exact mathematical model are discussed and a simplied solution is proposed. An exemplary algorithm is evaluated on three exemplary video sequences. The acquired...
-
Fire Protection and Materials Flammability Control by Artificial Intelligence
PublicationFire safety has become a major challenge of materials developers because of the massive production of organic materials, often combustibles, and their use for different purposes. In this sense, fire safety is critically considered in the development of engineering materials [1, 2]. The multiplicity of parameters contributing to the development of formulation of flame-retardant materials from one side and the sustainability concerns...
-
Artificial neural network based sensorless control ofinduction motor.
PublicationW artykule przedstawiono bezczujnikowy układ sterowania silnikiem indukcyjnym wykorzystujący sztuczne sieci neuronowe (ANN). Sieć neuronową wykorzystano w regulatorze prędkości silnika. Zaprezentowano wyniki badań symulacyjnych.
-
Numerical analysis of lumbar spine injury during road safety barrier collision
PublicationPurpose: Enhancing road safety is a critical goal worldwide, necessitating the development of clear standards for road safety systems. This study focuses on lumbar spine (L-spine) compression injuries during collisions with concrete road safety barriers (RSBs). It aims to analyze internal forces during impact to understand L-spine injury biomechanics in such accidents. Methods: The research included a literature review, analyzing...
-
TSR method for burns investigation approach
PublicationThe article presents the possibilities of applying the TSR method for the diagnosis of burn wounds. The wound area is stimulated by cold gas and a sequence of thermograms of heating the tissue is recorded. Next, TSR algorithms are used to determine the parameters that allow the wound to be classified into one of the classes: the wound heals within three weeks, the wound will not heal in three weeks. The method was...
-
Birch sap concentrate as a potential modern food product
PublicationThis paper presents birch sap concentrate obtained by the reverse osmosis method. It is characterized by sweet taste, high content of minerals and no risk to consumers in terms of content of heavy metals standardized in the European Union food legislation. This beverage has all the features of a modern food product, i.e. it has an attractive taste, is obtained using new technology, meets the clean label requirements and can be...
-
Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublicationIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
-
Architektury klasyfikatorów obrazów
PublicationKlasyfikacja obrazów jest zagadnieniem z dziedziny widzenia komputerowego. Polega na całościowej analizie obrazu i przypisaniu go do jednej lub wielu kategorii (klas). Współczesne rozwiązania tego problemu są w znacznej części realizowane z wykorzystaniem konwolucyjnych głębokich sieci neuronowych (convolutional neural network, CNN). W tym rozdziale opisano przełomowe architektury CNN oraz ewolucję state-of-the-art w klasyfikacji...
-
Differentiating patients with obstructive sleep apnea from healthy controls based on heart rate-blood pressure coupling quantified by entropy-based indices
PublicationWe introduce an entropy-based classification method for pairs of sequences (ECPS) for quantifying mutual dependencies in heart rate and beat-to-beat blood pressure recordings. The purpose of the method is to build a classifier for data in which each item consists of two intertwined data series taken for each subject. The method is based on ordinal patterns and uses entropy-like indices. Machine learning is used to select a subset...
-
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...
-
Jak sobie pościelisz… czyli o roli prac przedprojektowych
PublicationPrace przedprojektowe w inwestycjach liniowych. Przygotowanie procesu inwestycyjnego. Znaczenie poznania rzeczywistych warunków w jakich będzie prowadzony proces inwestycyjny. Ocena podłoża. Wymagania formalne, błędy. Błędy w ocenach cech materiałowych rozwiązań. Identyfikacja cech i warunków. Problemy wykonawstwa. Szczególne ryzyko.
-
Jakie będą oczyszczalnie 'jutra"?
PublicationRola oczyszczalni ścieków zaczyna wykraczać poza zapewnienie wysokiej efektywności usuwania zanieczyszczeń przy niskim wskaźniku zużycia energii. Obiekty te rozszerzają swoją funkcję w kierunku odzysku zasobów i stają się istotnymi elementami gospodarki o obiegu zamkniętym.
-
Projektowanie przestrzenne w nowej rzeczywistości
PublicationProblemy zmian zasad planowania zagospodarowania przestrzennego w aspekcie powtarzających się zjawisk powodziowych. Zmiany prawa wodnego, zmiana sposobu podejścia do zagadnienia. Konieczność zasadniczych zmian w planowaniu przestrzennym, w jego wszystkich fazach.
-
Wyznaczanie strefy ochronnej ujęcia wody
PublicationPotrzeba skutecznej ochrony ujęć wody ze szczególnym uwzględnieniem ujęć wody podziemnej. Braki w polskich regulacjach prawnych oraz praktyce. Potrzeba zmian i zasad postępowania. Propozycje rozwiązania problemu.
-
Accelerometer-based Human Activity Recognition and the Impact of the Sample Size
PublicationThe presented study focused on the recognition of eight user activities (e.g. walking, lying, climbing stairs) basing on the measurements from an accelerometer embedded in a mobile device. It is assumed that the device is carried in a specific location of the user’s clothing. Three types of classifiers were tested on different sizes of the samples. The influence of the time window (the duration of a single trial) on selected activities...
-
Affective reactions to playing digital games
PublicationThe paper presents a study of emotional states during a gameplay. An experiment of two-player Tetris game is reported, followed by the analysis of the results - self-reported emotional states as well as physiological signals measurements interpretation. The study reveals the diversity of emotional reactions and concludes, that a representative player's emotional model is hard to define. Instead, an adaptive approach to emotion...
-
Usefulness of Keystroke Dynamics Features in User Authentication and Emotion Recognition
PublicationThe study presented in the article focuses on keystroke dynamics analysis applied to recognize emotional states and to authenticate users. An overview of some studies and applications in these areas is presented. Then, an experiment is described, i.e. the way of collecting data, extracting features, training classifiers and finding out the most appropriate feature subsets. The results show that it is difficult to indicate a universal...
-
Monitoring of odour nuisance in the Tricity Agglomeration
PublicationThe paper describes a principle of operation of odour nuisance monitoring network, which is being designed in the Tricity Agglomeration. Moreover, it presents the preliminary results of an investigation on ambient air quality with respect to odour nuisance in a vicinity of the municipal landfill. The investigation was performed during spring-winter season using a prototype of electronic nose and the Nasal Ranger field olfactometers. The...
-
Comparison of the measurement techniques employed for evaluation of ambient air odour quality
PublicationThe paper presents the results of investigation on ambient air odour quality in a vicinity of the industrial sewage treatment plant being a part of the crude oil processing plant. The investigation was performed during spring-winter season using a prototype of electronic nose and the Nasal Ranger field olfactometers. The prototype was equipped with a set of six semiconductor sensors by FIGARO Co. and one PID-type sensor. The field...
-
Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...