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Wyniki wyszukiwania dla: 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
PublikacjaThe 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
PublikacjaThe 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
Dane BadawczeThe 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
Dane BadawczeThere 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
Dane BadawczeThe 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
PublikacjaEnglish 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
PublikacjaAn 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
PublikacjaImplementation 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
PublikacjaThe 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
PublikacjaThe 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
PublikacjaThe 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
PublikacjaThis 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
PublikacjaThe 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
PublikacjaEfficiency 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
PublikacjaAn 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
PublikacjaAn 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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Enhancing voice biometric security: Evaluating neural network and human capabilities in detecting cloned voices
PublikacjaThis study assesses speaker verification efficacy in detecting cloned voices, particularly in safety-critical applications such as healthcare documentation and banking biometrics. It compares deeply trained neural networks like the DeepSpeaker with human listeners in recognizing these cloned voices, underlining the severe implications of voice cloning in these sectors. Cloned voices in healthcare could endanger patient safety by...
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Evaluation of a Novel Approach to Virtual Bass Synthesis Strategy
PublikacjaThe 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
PublikacjaWe 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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The Use of Ultra-Fast Gas Chromatography for Fingerprinting-Based Classification of Zweigelt and Rondo Wines with Regard to Grape Variety and Type of Malolactic Fermentation Combined with Greenness and Practicality Assessment
PublikacjaIn food authentication, it is important to compare different analytical procedures and select the best method. The aim of this study was to determine the fingerprints of Zweigelt and Rondo wines through headspace analysis using ultra-fast gas chromatography (ultra-fast GC) and to compare the effectiveness of this approach at classifying wines based on grape variety and type of malolactic fermentation (MLF) as well as its greenness...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublikacjaWe 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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SYNAT_MUSIC_GENRE_FV_173
Dane BadawczeThis 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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Using Principal Component Analysis and Canonical Discriminant Analysis for multibeam seafloor characterisation data
PublikacjaThe 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
PublikacjaEnergy 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)
PublikacjaLake 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
PublikacjaThe 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
PublikacjaThe 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
PublikacjaAn 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
PublikacjaThe 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
PublikacjaOptimization-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
PublikacjaThe 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
PublikacjaTwelve 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
Publikacjaconvolutional 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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Antitumor Activity of Novel Benzensulfonamide Derivatives in View of their Physiochemical Properties Searched by Principal Component Analysis
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Rapid Yield Estimation and Optimization of Microwave Structures Exploiting Feature-Based Statistical Analysis
PublikacjaIn 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
PublikacjaThe 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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Monitoring the Uniformity of Fish Feeding Based on Image Feature Analysis
PublikacjaThe main purpose of the conducted research is the development and experimental verification of the methods for detection of fish feeding as well as checking its uniformity in the recirculating aquaculture systems (RAS) using machine vision. A particular emphasis has been set on the methods useful for rainbow trout farming. Obtained results, based on the analysis of individual video...
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Hyperelastic Microcantilever AFM: Efficient Detection Mechanism Based on Principal Parametric Resonance
PublikacjaThe 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
PublikacjaThis 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
PublikacjaIn 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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Fast Distance Vector Field Extraction for Facial Feature Detection
PublikacjaPraca 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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Examining Feature Vector for Phoneme Recognition / Analiza parametrów w kontekście automatycznej klasyfikacji fonemów
PublikacjaThe 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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Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling
PublikacjaPhoneme 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.
OsobySylwester Kaczmarek ukończył studia w 1972 roku jako mgr inż. Elektroniki, a doktorat i habilitację uzyskał z technik komutacyjnych i inżynierii ruchu telekomunikacyjnego w 1981 i 1994 roku na Politechnice Gdańskiej. Jego zainteresowania badawcze ukierunkowane są na: sieci IP QoS, sieci GMPLS, sieci SDN, komutację, ruting QoS, inżynierię ruchu telekomunikacyjnego, usługi multimedialne i jakość usług. Aktualnie jego badania skupiają...
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublikacjaThe 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
PublikacjaModern 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
PublikacjaAssessing 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
PublikacjaIn 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...