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Search results for: Principal Component Analysis-based feature vector
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Effective kernel‐principal component analysis based approach for wisconsin breast cancer diagnosis
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Music Recommendation System
PublicationThe paper focuses on optimization vector content feature for the music recommendation system. For the purpose of experiments a database is created consisting of excerpts of music les. They are assigned to 22 classes corresponding to dierent music genres. Various feature vectors based on low-level signal descriptors are tested and then optimized using correlation analysis and Principal Component Analysis (PCA). Results of the experiments...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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SYNAT Music Genre Parameters PCA 19
Open Research DataThe dataset contains feature vector after Principal Component Analysis (PCA) performing, so there are 11 music genres and 19-element vector derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of 52532 music excerpts described...
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SYNAT_PCA_48
Open Research DataThere is a series of datasets containing feature vectors derived from music tracks. The dataset contains 51582 music tracks (22 music genres) and feature vector after Principal Component Analysis (PCA) performing, so there are 48-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier...
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SYNAT_PCA_11
Open Research DataThe dataset contains 51582 music tracks (22 music genres) and feature vector after Principal Component Analysis (PCA) performing, so there are 11-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of more than...
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Selection of Features for Multimodal Vocalic Segments Classification
PublicationEnglish speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...
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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...
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Remote Health Monitoring of Wind Turbines Employing Vibroacoustic Transducers and Autoencoders
PublicationImplementation of remote monitoring technology for real wind turbine structures designed to detect potential sources of failure is described. An innovative multi-axis contactless acoustic sensor measuring acoustic intensity as well as previously known accelerometers were used for this purpose. Signal processing methods were proposed, including feature extraction and data analysis. Two strategies were examined: Mel Frequency Cepstral...
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Music Data Processing and Mining in Large Databases for Active Media
PublicationThe aim of this paper was to investigate the problem of music data processing and mining in large databases. Tests were performed on a large data-base that included approximately 30000 audio files divided into 11 classes cor-responding to music genres with different cardinalities. Every audio file was de-scribed by a 173-element feature vector. To reduce the dimensionality of data the Principal Component Analysis (PCA) with variable...
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Self-Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
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Self–Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
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Computational complexity and length of recorded data for fluctuation enhanced sensing method in resistive gas sensors
PublicationThis paper considers complexity and accuracy of data processing for gas detection using resistance fluctuation data observed in resistance gas sensors. A few selected methods were considered (Principal Component Analysis – PCA, Support Vector Machine – SVM). Functions like power spectral density or histogram were used to create input data vector for these algorithms from the observed resistance fluctuations. The presented considerations...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublicationThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Efficiency of gas detection algorithms using fluctuation enhanced sensing
PublicationEfficiency of various gas detection algorithms by applying fluctuation enhanced sensing method was discussed. We have analyzed resistance noise observed in resistive WO3- nanowires gas sensing layers. Power spectral densities of the recorded noise were used as the input data vectors for two algorithms: the principal component analysis (PCA) and the support vector machine (SVM). The data were used to determine gas concentration...
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A comparative study of English viseme recognition methods and algorithms
PublicationAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector construction...
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A comparative study of English viseme recognition methods and algorithm
PublicationAn elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector...
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Evaluation of a Novel Approach to Virtual Bass Synthesis Strategy
PublicationThe aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) strategy applied to portable computers. The developed algorithms involve intelligent, rule-based settings of bass synthesis parameters with regard to music genre of an audio excerpt and the type of a portable device in use. The Smart VBS algorithm performs the synthesis based on a nonlinear device (NLD) with artificial controlling synthesis...
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Noise sources in Raman spectroscopy of biological objects
PublicationWe present an overview of noise sources deteriorating the quality of the recorded biological Raman spectra and the ability to determine the specimen composition. The acquired Raman spectra exhibit intense additive noise components or drifts because of low intensity of the scattered light. Therefore we have to apply expensive or bulky measurement setups to limit their inherent noise or to apply additional signal processing to reduce...
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SYNAT_MUSIC_GENRE_FV_173
Open Research DataThis is the original dataset containing 51582 music tracks (22 music genres) and 173 element-feature vector [1-6,9]. A collection of more than 50000 music excerpts described with a set of descriptors obtained through the analysis of 30-second mp3 recordings was gathered in a database called SYNAT. The SYNAT database was realized by the Gdansk University...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublicationWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data
PublicationThe paper presents the seafloor characterisation based on multibeam sonar data. It relies on using the integrated model and description of three types of multibeam data obtained during seafloor sensing: 1) the grey-level sonar images (echograms) of seabed, 2) the 3D model of the seabed surface which consists of bathymetric data, 3) the set of time domain bottom echo envelopes received in the consecutive sonar beams. The classification...
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A hybrid approach to optimization of radial inflow turbine with principal component analysis
PublicationEnergy conversion efficiency is one of the most important features of power systems as it greatly influences the economic balance. The efficiency can be increased in many ways. One of them is to optimize individual components of the power plant. In most Organic Rankine Cycle (ORC) systems the power is created in the turbine and these systems can benefit from effective turbine optimization. The paper presents the use of two kinds...
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A High-Arctic flow-through lake system hydrochemical changes: Revvatnet, southwestern Svalbard (years 2010–2018)
PublicationLake ecosystems are strongly coupled to features of their surrounding landscapes such as geomorphology, lithology, vegetation and hydrological characteristics. In the 2010–2018 summer seasons, we investigated an Arctic flow-through lake system Revvatnet, located in the vicinity of the coastal zone of Hornsund fjord in Svalbard, characterising its hydrological properties and the chemical composition of its waters. The lake system...
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Multispectral impedance quality testing of coil-coating system using principal component analysis
PublicationThe task of quality checking of the coil-coated system was undertaken using impedance spectroscopy. In order to properly characterize the system the new impedance spectrum was calculated as an averaged result of 12 experimental spectra obtained from 12 different places of the sample at the same time of immersion in 3% of NaCl. The experimental spectra were recorded for a 24-h period at 1 h intervals between starting points of each...
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Determination of time dependence of coated metal electrical and electrochemical parameters during exposure using principal component analysis
PublicationThe use of the principal component analysis (PCA) permits the complex and quantitative analysis of the time dependence of electrical and electrochemical parameters of coated metal obtained by fitting impedance data. So far, changes in electrical and electrochemical parameters during exposure were analyzed independently. In this way, some of the information contained in the relationship between changes in parameters over time are...
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Quantification of Compatibility Between Polymeric Excipients and Atenolol Using Principal Component Analysis and Hierarchical Cluster Analysis
PublicationAn important challenge to overcome in the solid dosage forms technology is the selection of the most biopharmaceutically efficient polymeric excipients. The excipients can be selected, among others, by compatibility studies since incompatibilities between ingredients of the drug formulations adversely affect their bioavailability, stability, efficacy, and safety. Therefore, new, fast, and reliable methods for detecting incompatibility...
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Nonlinear principal component analysis of the tidal dynamics in a shallow sea
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Examining Feature Vector for Phoneme Recognition
PublicationThe aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...
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Expedited Design Closure of Antenna Input Characteristics by Trust Region Gradient Search and Principal Component Analysis
PublicationOptimization-based parameter tuning has become an inherent part of contemporary antenna design process. For the sake of reliability, it is typically conducted at the level of full-wave electromagnetic (EM) simulation models. This may incur considerable computational expenses depending on the cost of an individual EM analysis, the number of adjustable variables, the type of task (local, global, single-/multi-objective optimization),...
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Application of principal component and hierarchical cluster analysis in classifying defects of trolleybuses
PublicationThe failure rate of vehicles is a relevant task, which is strictly connected with the reliability of transportation systems. Methods of data analysis allow us to find similarity and differences between failure rates of several parts of trolleybuses. This paper deals with the statistic of failure of trolleybuses from the municipal transport company of Gdynia (Poland).
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Characterization of 1,3-alternate calix[4]arene-silica bonded stationary phases and their comparison to selected commercial columns by using principal component analysis
PublicationTwelve calix[4]arene stationary phases in 1,3-alternate conformation, synthesized in the authors laboratory, were characterized in terms of their surface coverage, hydrophobic selectivity, aromatic selectivity, shape selectivity, hydrogen bonding capacity and ion-exchange capacity. The set of tests commonly used for evaluation of commercially available stationary phases was applied to assess fundamental chromatographic properties...
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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...
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Rapid Yield Estimation and Optimization of Microwave Structures Exploiting Feature-Based Statistical Analysis
PublicationIn this paper, we propose a simple, yet reliable methodology to expediteyield estimation and optimization of microwave structures. In our approach,the analysis of the entire response of the structure at hand (e.g., $S$-parameters asa function of frequency) is replaced by response surface modeling of suitablyselected feature points. On the one hand, this is sufficient to determinewhether a design satisfies given performance specifications....
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Determining the leakage current resistive component by the orthogonal vector method
PublicationThe measurement of the metal – oxide surge arresters (MOSA) leakage current and the analysis of its components is a key diagnostic criterion according to technical standards. During on site MOSA condition assessment, the easy way is based on the measurement only leakage current, without the inconvenient live working measurements of supply voltage. Orthogonal vectors method of determination the resistive leakage current is presented....
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Hyperelastic Microcantilever AFM: Efficient Detection Mechanism Based on Principal Parametric Resonance
PublicationThe impetus of writing this paper is to propose an efficient detection mechanism to scan the surface profile of a micro-sample using cantilever-based atomic force microscopy (AFM), operating in non-contact mode. In order to implement this scheme, the principal parametric resonance characteristics of the resonator are employed, benefiting from the bifurcation-based sensing mechanism. It is assumed that the microcantilever is made...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Formulation of Time-Fractional Electrodynamics Based on Riemann-Silberstein Vector
PublicationIn this paper, the formulation of time-fractional (TF) electrodynamics is derived based on the Riemann-Silberstein (RS) vector. With the use of this vector and fractional-order derivatives, one can write TF Maxwell’s equations in a compact form, which allows for modelling of energy dissipation and dynamics of electromagnetic systems with memory. Therefore, we formulate TF Maxwell’s equations using the RS vector and analyse their...
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Examining Feature Vector for Phoneme Recognition / Analiza parametrów w kontekście automatycznej klasyfikacji fonemów
PublicationThe aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...
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Fast Distance Vector Field Extraction for Facial Feature Detection
PublicationPraca dotyczy metody lokalizowania cech twarzy z wykorzystaniem wektorowych pól odległości (DVF), zaproponowanej przez Asteriadisa. Zawiera skrótowy opis tej koncepcji oraz prezentuje ulepszenia wprowadzone przez autorów do oryginalnego rozwiązania. Główną zaletą wprowadzonych zmian jest znacznie zredukowana złożoność obliczeniowa algorytmu, jak również zwiększona precyzja wektorowego pola odległości wyznaczanego w wyniku jego...
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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublicationPhoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...
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Sylwester Kaczmarek dr hab. inż.
PeopleSylwester Kaczmarek received his M.Sc in electronics engineering, Ph.D. and D.Sc. in switching and teletraffic science from the Gdansk University of Technology, Gdansk, Poland, in 1972, 1981 and 1994, respectively. His research interests include: IP QoS and GMPLS and SDN networks, switching, QoS routing, teletraffic, multimedia services and quality of services. Currently, his research is focused on developing and applicability...
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublicationThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Computationally-Efficient Statistical Design and Yield Optimization of Resonator-Based Notch Filters Using Feature-Based Surrogates
PublicationModern microwave devices are designed to fulfill stringent requirements pertaining to electrical performance, which requires, among others, a meticulous tuning of their geometry parameters. When moving up in frequency, physical dimensions of passive microwave circuits become smaller, making the system performance increasingly susceptible to manufacturing tolerances. In particular, inherent inaccuracy of fabrication processes affect...
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Tolerance-Aware Multi-Objective Optimization of Antennas by Means of Feature-Based Regression Surrogates
PublicationAssessing the immunity of antenna design to fabrication tolerances is an important consideration, especially when the manufacturing process has not been predetermined. At the same time, the antenna parameter tuning should be oriented toward improving the performance figures pertinent to both electrical (e.g., input matching) and field properties (e.g., axial ratio bandwidth) as much as possible. Identification of available trade-offs...
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RSS-Based DoA Estimation for ESPAR Antennas Using Support Vector Machine
PublicationIn this letter, it is shown how direction-of-arrival (DoA) estimation for electronically steerable parasitic array radiator (ESPAR) antennas, which are designed to be integrated within wireless sensor network nodes, can be improved by applying support vector classification approach to received signal strength (RSS) values recorded at an antenna's output port. The proposed method relies on ESPAR antenna's radiation patterns measured...
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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublicationIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Rotor-Flux Vector based Observer of Interior Permanent Synchronous Machine
PublicationThe sensorless control system of the interior permanent magnet machine is considered in this paper. The control system is based on classical linear controllers. In the machine, there occurs non-sinusoidal distribution of rotor flux together with the slot harmonics, which are treated as the control system disturbances. In this case, the classical observer structure in the (d-q) is unstable for the low range of rotor speed resulting...
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Kinetic flux vector splitting scheme for solving non-reactive multi-component flows
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Phylogenetic trees of genus Oncidium Sw. based on analysis of DNA sequences
Open Research DataGenus Oncidium Sw. is widely regarded as a polyphiletic, and the taxonomic boundaries between him and such genera as Odontoglossum Kunth. or Miltonia Lindley remain blurred. The goal of the study was to determine the phylogenetic relationships within the genus Oncidium s.lato based on the DNA sequences analysis. The correlation between molecular data...
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Application of discriminant analysis to feature extraction.
PublicationPierwotnie uzyskiwane wektory cech są wysokowymiarowe. Redukcja wymiarowości jest często osiągana poprzez transformacje przestrzeni cech. Niniejsza praca prezentuje uogólnione kryterium Fishera i jego podstawowe własności, dyskutowana jest także możliwość wyprowadzania i oceny heurystycznych metod ekstrakcji cech. Przedstawiono również nowy sekwencyjny algorytm selekcji cech dyskryminacyjnych.
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Multi-Criterial Design of Antennas with Tolerance Analysis Using Response-Feature Predictors
PublicationImperfect manufacturing is one of the factors affecting the performance of antenna systems. It is particularly important when design specifications are strict and leave a minimum leeway for a degradation caused by geometry or material parameter deviations from their nominal values. At the same time, conventional antenna design procedures routinely neglect to take the fabrication tolerances into account, which is mainly a result...
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Variable-fidelity response feature surrogates for accelerated statistical analysis and yield estimation of compact microwave components
PublicationAccounting for manufacturing tolerances is an essential part of a reliable microwave design process. Yet, quantification of geometry and/or material parameter uncertainties is challenging at the level of full-wave electromagnetic (EM) simulation models. This is due to inherently high cost of EM analysis and massive simulations necessary to conduct the statistical analysis. Here, a low-cost and accurate yield estimation procedure...
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Rapid design closure of microwave components by means of feature-based optimization and adjoint sensitivities
PublicationIn this article, fast design closure of microwave components using feature-based optimization (FBO) and adjoint sensitivities is discussed. FBO is one of the most recent optimization techniques that exploits a particular structure of the system response to “flatten” the functional landscape handled during the optimization process, which leads to reducing its computational complexity. When combined with gradient-based search involving...
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Machining process sequencing and machine assignment in generative feature-based CAPP for mill-turn parts
PublicationProcess selection and sequencing, as one of the most complex issues when evaluated from a mathematical point of view and crucial in CAPP, still attract research attention. For the current trend of intelligent manufacturing, machining features (MFs) are the information carriers for workpiece geometry and topology representation. They are basically derived from CAD models and are used by downstream engineering applications. A feature-based...
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Current based Normalized Triple Covariance as a bearings diagnostic feature in induction motor
PublicationDiagnosis of induction motors, conducted remotely by measuring and analyzing the supply current is attractive with the lack of access to the engine. So far there is no solution, based on analysis of current, the credibility of which allow use in industry. Statistics of IM bearing failures of induction motors indicate, that they constitute more than 40% of IM damage, therefore bearing diagnosis is so important. The article provides...
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Current-based higher-order spectral covariance as a bearing diagnostic feature for induction motors
PublicationConducting the diagnosis of induction motors remotely by analyzing the supply current is an attractive prospect with the lack of access to the engine. Currently, there is no solution, based on analysis of the current, the credibility of which would allow its use in industry. The statistics of bearing failures in induction motors indicate that they constitute more than 40% of induction motor damage, therefore, bearing diagnosis...
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Virtual Space Vector Pulse Width Modulation Algorithm for Three-Level NPC Converters Based on the Final Element Shape Functions
PublicationThe paper puts forth a novel idea for the computation of Nearest Three Virtual Space Vector Pulse Width Modulation for the three level NPC converters. The computations are based on the concept of final element shape function widely used in the domain of finite element analysis. The proposed approach significantly frees the computations from the use of trigonometric functions, which simplifies the computations and permits easier...
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Rime samples characterization and comparison using classical and fuzzy principal components analysis
PublicationEfektywność dwóch nowych algorytmów w stosunku do klasycznego wariantu techniki PCA porównano analizując dane dotyczące zanieczyszczeń próbek sadzi zebranych na terenie trzech stacji w okresie 2004-2007. Zastosowane algorytmy FPCA-1 i FPCA-o pozwalają na wyodrębnienie większej liczby miejsc zbierania próbek i analitów w stosunku do sytuacji, kiedy stosuje się klasyczny wariant techniki PCA.
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
PublicationThe aim of this paper is to present a novel method, called Adaptive Edge Detection (AED), of extraction of precise pupil edge coordinates from eye image characterized by reflections of external illuminators and laser beams. The method is used for monitoring of pupil size and position during psychophysical tests of two-photon vision performed by dedicated optical set-up. Two-photon vision is a new phenomenon of perception of short-pulsed...
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A New Three-Dimensional Space Vector Modulation for Multilevel Four-Leg Converters Based on the Shape Functions of Tetrahedral Element
PublicationThe paper proposes a new three-dimensional space vector pulse-width modulation (3D-SVPWM) algorithm for multilevel four-leg converters. The proposed PWM duty cycle calculation is based on the shape functions of the threedimensional tetrahedral finite elements. The algorithm ensures synthesis of accurate and undistorted output voltages even under significant imbalance or ripple in the DC-link voltages. At the same time, the algorithm...
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Auditory-model based robust feature selection for speech recognition
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Global EM-Driven Optimization of Multi-Band Antennas Using Knowledge-Based Inverse Response-Feature Surrogates
PublicationElectromagnetic simulation tools have been playing an increasing role in the design of contemporary antenna structures. The employment of electromagnetic analysis ensures reliability of evaluating antenna characteristics but also incurs considerable computational expenses whenever massive simulations are involved (e.g., parametric optimization, uncertainty quantification). This high cost is the most serious bottleneck of simulation-driven...
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SiC-based phase-shift dual half bridge DC-DC converter as a key component of multilevel cascaded MV converters
PublicationThe paper describes SiC-based dual half bridge (DHB) DC-DC converter considered as a key component of high frequency isolated multilevel cascaded medium voltage converters. Two topologies of bi-directional DC-DC converters: the resonant half-bridge DC-DC converter and the phase-shift DHB converter are compared in the paper. Experimental results of SiC-based 50 kHz DHB DC-DC converter are presented in the paper.
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Design-oriented computationally-efficient feature-based surrogate modelling of multi-band antennas with nested kriging
PublicationDesign of modern antenna structures heavily depends on electromagnetic (EM) simulation tools. EM analysis provides reliable evaluation of increasingly complex designs but tends to be CPU intensive. When multiple simulations are needed (e.g., for parameters tuning), the aggregated simulation cost may become a serious bottleneck. As one possible way of mitigating the issue, the recent literature fosters utilization of faster representations,...
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Structure and the space vector modulation for a medium-voltage power-electronic-transformer based on two seven-level cascade H-bridge inverters
PublicationThis study presents the structure and the space vector pulse-width modulation (SVPWM) for power electronic transformer (PET) based on two seven-level cascade H-bridge (CHB) inverters. The DC links of CHB inverters are coupled with nine dual-active bridge (DAB) converters with medium-frequency transformers. The DC-link voltages are equalised with two methods – through the control of DAB voltages...
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The dimensions of national competitiveness: the empirical analysis based on The World Economic Forum’s data
PublicationThe aim of this research is to determine the minimum number of uncorrelated dimensions which can describe national competitiveness (NC). NC is thought of as the ability of a nation to provide a conducive environment for its firms to prosper. It is shown that the environment affects national productivity catalytically through the interactions with the production factors while itself remaining unchanged. Selected World Economic...
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Improved Procedures for Feature-Based Suppression of Surface Texture High-Frequency Measurement Errors in the Wear Analysis of Cylinder Liner Topographies
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Data Sampling-Based Feature Selection Framework for Software Defect Prediction
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Feature-based generation of machining process plans for optimised parts manufacture
PublicationPrzedstawiono aktualne zagadnienia związane z integracją systemów CAD/CAM/CAPP. Opracowano model informacyjny danych dla systemu CAPP w postaci zapisu macierzowego. Zawarto algorytm tworzenia rozwiązań wariantowych i wyboru optymalnego procesu technologicznego obróbki. Proponowany algorytm działania zweryfikowano na rzeczywistym przykładzie z praktyki przemysłu.
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Agent-Based RBF Network Classifier with Feature Selection in a Kernel Space
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Cluster-dependent rotation-based feature selection for the RBF networks initialization
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Calibration of acoustic vector sensor based on MEMS microphones for DOA estimation
PublicationA procedure of calibration of a custom 3D acoustic vector sensor (AVS) for the purpose of direction of arrival (DoA) estimation, is presented and validated in the paper. AVS devices working on a p-p principle may be constructed from standard pressure sensors and a signal processing system. However, in order to ensure accurate DoA estimation, each sensor needs to be calibrated. The proposed algorithm divides the calibration process...
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublicationOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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IPMSM rotor position estimator based on analysis of phase current derivatives
PublicationThis paper describes an algorithm for estimation of IPMSM angular rotor position. The algorithm uses derivatives of motor phase currents resulting from PWM modulation to obtain the rotor position. The presented method is designed for medium- and high-speed range, since it is based on determination of the EMF vector. Algorithm is characterised by a very simple formulae. The calculation of rotor position is performed in every PWM...
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Multidimensional Feature Selection and Interaction Mining with Decision Tree Based Ensemble Methods
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Fast Design Closure of Compact Microwave Components by Means of Feature-Based Metamodels
PublicationPrecise tuning of geometry parameters is an important consideration in the design of modern microwave passive components. It is mandatory due to limitations of theoretical design methods unable to quantify certain phenomena that are important for the operation and performance of the devices (e.g., strong cross-coupling effects in miniaturized layouts). Consequently, the initial designs obtained using analytical or equivalent network...
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Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
PublicationThis paper aims to propose complex Morlet (cmorfb-fc) wavelet-based refined damage-sensitive feature (rDSF) as a new and more precise damage indicator to diagnose seismic damages in adjacent steel and Reinforced Concrete (RC) Moment Resisting Frames (MRFs) assuming pounding conditions using acceleration responses. The considered structures include 6- and 9-story steel and 4- and 8-story RC benchmark MRFs that are assumed to have...
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Development of fragility curves in adjacent steel moment-resisting frames considering pounding effects through improved wavelet-based refined damage-sensitive feature
PublicationFragility curves present useful information related to earthquake-induced probability assessment of steel moment-resisting frames (MRFs) and determine the probability of the damage exceedance at different floor levels of MRFs. The review of the literature shows that most of the previous studies dealing with the fragility curves were based on conventional measures, such as spectral acceleration at the first mode period, peak...
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Performance analysis of power swing blocking feature in ABB 670 series impedance relays
PublicationThis paper presents test results of a distance protection’s PSD power swing detection feature in ABB 670 series relays. A RED670 relay was tested, which is part of the hydroelectric set protection in Żarnowiec Pumped Storage Plant. The power swing blocking feature’s performance was analysed on the basis of the results of object tests made with an Omicron digital tester. Also presented are simulation results that illustrate the...
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Feature-Based Characterisation of Turned Surface Topography with Suppression of High-Frequency Measurement Errors
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A cortex-like model for animal recognition based on texture using feature-selective hashing
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Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
PublicationThis paper aims to propose complex Morlet (cmorfb-fc) wavelet-based refined damage-sensitive feature (rDSF) as a new and more precise damage indicator to diagnose seismic damages in adjacent steel and Reinforced Concrete (RC) Moment Resisting Frames (MRFs) assuming pounding conditions using acceleration responses. The considered structures include 6- and 9-story steel and 4- and 8-story RC benchmark...
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STUDYING THE PROCESS OF OBTAINING PHOSPHATES OF METALS BASED ON THE PHASE EQUILIBRIA OF FOUR COMPONENT SYSTEMS
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Physico-chemical properties of three-component mixtures based on chitosan, hyaluronic acid and collagen
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Enhancement of PUR/PIR foam thermal stability after addition of Zostera marina biomass component investigated via thermal analysis and isoconversional kinetics
PublicationIn the present work, a thorough thermogravimetric (TG) analysis of bio-based polyurethane–polyisocyanurate (PUR–PIR) foams in both nitrogen and oxygen atmosphere is performed. A sustainable element of the foam is a biopolyol obtained via acid-catalyzed liquefaction of Zostera marina and Enteromorpha Algae biomass. Based on isoconversional analysis and apparent activation energies, several conclusions are obtained. In contradiction...
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BADANIE EFEKTYWNOŚCI WYKRYWANIA ANOMALII PROCESOWYCH W DZIAŁANIU TURBINY PAROWEJ ELEKTROWNI JĄDROWEJ PRZY POMOCY METOD WIELOWYMIAROWEJ ANALIZY STATYSTYCZNEJ
PublicationW artykule przedstawiono analizę możliwości wykrywania anomalii procesowych w działaniu turbiny parowej elektrowni jądrowej przy pomocy metod wielowymiarowej analizy statystycznej. Zasymulowano symptomy dwóch rodzajów uszkodzeń turbiny parowej tj. uderzenie wodne oraz, wyciek pary z zaworu części niskoprężnej. Jako narzędzie diagnostyczne wykorzystano Metodę Składników Podstawowych PCA (z ang. Principal Component Analysis). Jako...
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Pupil detection supported by Haar feature based cascade classifier for two-photon vision examinations
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Aleksandra Parteka dr hab. inż.
PeopleAbout me: I am an associate professor and head of doctoral studies at the Faculty of Management and Economics, Gdansk University of Technology (GdanskTech, Poland). I got my MSc degree in Economics from Gdansk University of Technology (2003) and Universita’ Politecnica delle Marche (2005), as well as MA degree in Contemporary European Studies from Sussex University (2006, with distinction). I received my PhD in Economics...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublicationA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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Application of gas chromatography to the analysis of spirit-based alcoholic beverages
PublicationSpirit-based beverages are alcoholic drinks, which production processes are dependent on the type and origin of raw materials. The composition of this complex matrix is difficult to analyze and scientists commonly choose a gas chromatography techniques for this reason. With a wide selection of extraction methods and detectors it is possible to provide qualitative and quantitative analysis for many chemical compounds with a various...
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Component Based Flight Simulation in DIS Systems.Komponentowy model symulacji obiektów latających w systemach DIS.
PublicationInteraktywna symulacja rozproszona stanowi interesującą klasę systemów informacyjnych łączących kilka dziedzin informatyki pozwalających każdemu obiektowi na indywidualne symulowanie dla wizualizacji dynamicznego stanu wszystkich uczestniczących w symulacji obiektów rozproszonych. Obiekty są nieprzewidywalne, z tego powodu istnieje konieczność ciągłej wymiany informacji o ich stanie na potrzeby poprawnej wizualizacji 3D sceny z...
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Barrett-Joyner-Halenda (BJH) and Brunauer-Emmett-Teller (BET) analysis of wood and straw based biochars
Open Research DataThis data set includes the BJH and BET analysis results for straw and wood chips-based biochars generated at 450 Celsius degrees.
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Analysis of allophones based on audio signal recordings and parameterization
PublicationThe aim of this study is to develop an allophonic description of English plosive consonants based on recordings of 600 specially selected words. Allophonic variations addressed in the study may have two sources: positional and contextual. The former one depends on the syllabic or prosodic position in which a particular phoneme occurs. Contextual allophony is conditioned by the local phonetic environment. Co-articulation overlapping...
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XPS analysis of the GO based materials
Open Research DataGraphene oxides samples were measured by XPS method. The X-ray photoemission spectroscopy measurements were carried out with Omicron NanoTechnology UHV equipment. The hemispherical spectrophotometer was equipped with a 128-channel collector. The XPS measurements were performed at room temperature at a pressure below 1.1 × 10−8 mBar. The photoelectrons...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Decisional-DNA Based Smart Production Performance Analysis Model
Publicationn order to allocate resources effectively according to the production plan and to reduce disturbances, a framework for smart production performance analysis is proposed in this article. Decisional DNA based knowledge models of engineering objects, processes and factory are developed within the proposed framework. These models are the virtual representation of manufacturing resources, and with help of Internet of Things, are capable...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...