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Search results for: FEATURE WEIGHTED ATTENTION
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Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych
PublicationThe aim of this article is to investigate whether separating music tracks at the pre-processing phase and extending feature vector by parameters related to the specific musical instruments that are characteristic for the given musical genre allow for efficient automatic musical genre classification in case of database containing thousands of music excerpts and a dozen of genres. Results of extensive experiments show that the approach...
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Employment of passive sampling in monitoring indoor air quality in selected residences in a Tri-city area in Poland
PublicationTime-weighted average concentrations of selected volatile compounds were measured in chosen residences in a Tri-City area of Poland by means of passive sampling. The results were compared to those obtained by dynamic technique – sorption tubes filled with Tenax TA sorbent. Results obtained by employing the two techniques were similar. Total volatile organic compound (TVOC) parameters were also determined. An attempt was also...
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Using phase of short-term Fourier transform for evaluation of spectrogram performance
PublicationThe concept of spectrogram performance evaluation which exploits information on phase of short-term Fourier transform (STFT) is presented. A spectrograph which is time-frequency analyzing tool, is compared to a filter bank that demultiplexes a signal. Local group delay (LGD) and channelized instantaneous frequency (CIF) is obtained for each filtered component signal. In presented solution the performance is evaluated using so-called...
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Mean drift detection using statistical process control
PublicationCelem niniejszego rozdziału jest opisanie narzędzi statystycznej kontroli procesu (ang. Statistical Process Control - SPC), służących do detekcji dryfu wartości średniej w procesie. W oparciu o dane pochodzące z modelu: karty wartości średniej, odchylenia standardowego, karty oparte na testach sekwencyjnych oraz wykładniczo ważonej średniej ruchomej (ang. Exponentially Weighted Moving Average - EWMA), zostały porównane z punktu...
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Nanodiamonds Doped with Manganese for Applications in Magnetic Resonance Imaging
PublicationNanodiamonds (NDs) are emerging with great potential in biomedical applications like biomarking through fluorescence and magnetic resonance imaging (MRI), targeted drug delivery, and cancer therapy. The magnetic and optical properties of NDs could be tuned by selective doping. Therefore, we report multifunctional manganese-incorporated NDs (Mn-NDs) fabricated by Mn ion implantation. The fluorescent properties of Mn-NDs were tuned...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublicationSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Shared processor scheduling of multiprocessor jobs
PublicationWe study a problem of shared processor scheduling of multiprocessor weighted jobs. Each job can be executed on its private processor and simultaneously on possibly many processors shared by all jobs. This simultaneous execution reduces their completion times due to the processing time overlap. Each of the m shared processors may charge a different fee but otherwise the processors are identical. The goal is to maximize the total...
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Spectroscopy Methods in Nanotechnology 2023
e-Learning CoursesCourse for 2nd degree Students of Nanotechnology, specialization Nanostructures and computer simulations in materials science, sem. 2. The aim of the course is to discuss the basic theoretical and practical issues of spectroscopy and presentation of the various types of spectroscopic methods and ways to interpret spectra, with particular attention paid to the possibility of their use in the study of nanostructured systems.
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Spectroscopy Methods in Nanotechnology 2022
e-Learning CoursesCourse for 2nd degree Students of Nanotechnology, specialization Nanostructures and computer simulations in materials science, sem. 2. The aim of the course is to discuss the basic theoretical and practical issues of spectroscopy and presentation of the various types of spectroscopic methods and ways to interpret spectra, with particular attention paid to the possibility of their use in the study of nanostructured systems.
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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Selected Features of Dynamic Voting
PublicationIn multi-agent systems composed of autonomous agents with local knowledge, it is often desirable to aggregate their knowledge in order to make an educated decision. One of the methods of agreeing to a common decision is voting. A new history-based dynamic weight protocol allows for identification of the agents which contribute to the correct system decision. The main advantage of this approach, compared to static weighted system...
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Reliable Microwave Modeling By Means of Variable-Fidelity Response Features
PublicationIn this work, methodologies for low-cost and reliable microwave modeling are presented using variable-fidelity response features. The two key components of our approach are: (i) a realization of the modeling process at the level of suitably selected feature points of the responses (e.g., S-parameters vs. frequency) of the structure at hand, and (ii) the exploitation of variable-fidelity EM simulation data, also for the response...
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Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering
PublicationThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. Online tracking of signal model parameters is performed using the exponential ly weighted least squares algo- rithm. Detection of noise pulses an d model-based interpolation of the irrevocably distorted sampl es is realized using an adaptive, variable-order...
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Quality of Test Specification by Application of Patterns
PublicationEmbedded system and software testing requires sophisticated methods, which are nowadays frequently supported by application of test patterns. This eases the test development process and contributes to the reusability and maintainability of the test specification. However, it does not guarantee the proper level of quality and test coverage in d ifferent dimensions of the test specification. In this paper the quality of the test...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification
PublicationLand Use and Land Cover (LULC) monitoring is crucial for global transformation, sustainable land control, urban planning, urban growth prediction, and the establishment of climate regulations for long-term development. Remote sensing images have become increasingly important in many environmental planning and land use surveys in recent times. LULC is evaluated in this research using the Sat 4, Sat 6, and Eurosat datasets. Various...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Area covered by dominant tree species in the State Forests divided into stand age classes over the years 2014-2018
Open Research DataThe dataset contains data illustrating changes in distribution of dominant tree species in the State Forests divided into stand age classes over the years 2014-2018. Information about covered area is provided in ha and percentage of whole analyzed area. Dominant speciescan be defined as the species in the stand with the largest share in terms of area,...
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Area covered by dominant tree species in the State Forests divided into stand age classes over the years 2019-2023
Open Research DataThe dataset contains data illustrating changes in distribution of dominant tree species in the State Forests divided into stand age classes over the years 2019-2023. Information about covered area is provided in ha and percentage of whole analyzed area. Dominant speciescan be defined as the species in the stand with the largest share in terms of area,...
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Implementation of Non-Probabilistic Methods for Stability Analysis of Nonlocal Beam with Structural Uncertainties
PublicationIn this study, a non-probabilistic approach based Navier’s Method (NM) and Galerkin Weighted Residual Method (GWRM) in term of double parametric form has been proposed to investigate the buckling behavior of Euler-Bernoulli nonlocal beam under the framework of the Eringen's nonlocal elasticity theory, considering the structural parameters as imprecise or uncertain. The uncertainties in Young’s modulus and diameter of the beam are...
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Selection of Relevant Features for Text Classification with K-NN
PublicationIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...
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Biometric identity verification
PublicationThis chapter discusses methods which are capable of protecting automatic speaker verification systems (ASV) from playback attacks. Additionally, it presents a new approach, which uses computer vision techniques, such as the texture feature extraction based on Local Ternary Patterns (LTP), to identify spoofed recordings. We show that in this case training the system with large amounts of spectrogram patches may be difficult, and...
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublicationIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
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On noncausal identification of nonstationary stochastic systems
PublicationIn this paper we consider the problem of noncausal identification of nonstationary,linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing...
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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublicationAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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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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Can we really solve an arch stability problem?
PublicationWe bring attention to the problem of solving nonlinear boundary-value problems for elastic structures such as arches and shells. Here we discuss a classical problem of a shear-deformable arch postbuckling. Considering a postbuckling behaviour of a circular arch we discuss the possibility to find numerically a solution for highly nonlinear regimes. The main attention is paid to the problem of determination of all solutions. The...
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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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Classifying type of vehicles on the basis of data extracted from audio signal characteristics
PublicationThe aim of this study is to find and optimize a feature vector for an automatic recognition of the type of vehicles, extracted form an audio signal. First, the influence of weather-based conditions of road surface on spectral characteristic of the audio signal recorded from a passing vehicle in close proximity to the road is discussed. Next, parameterization of the recorded audio signal is performed. For that purpose, the MIRtoolbox,...
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Microalgal strains from the Culture Collection of Baltic Algae (CCBA)
Open Research DataThe dataset contains information on the cyanobacterial and microalgal strains maintained at the Culture Collection of Baltic Algae (CCBA) at the Institute of Oceanography UG. The collection maintains cyanobacterial and algal strains isolated from the Baltic Sea and additionally several strains collected from a wide range of habitats. The culture collection...
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Attitudes to tree removal on private properties in two Polish cities.
Open Research DataLarge cities are increasingly faced with declining urban tree cover and related problems, such as increased urban heat islands and flash floods. Reducing these phenomena increasingly has to rely on trees located on private property. However, to effectively engage private landowners on these issues, more attention must be paid to understanding their...
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On optimal tracking of rapidly varying telecommunication channels
PublicationWhen parameters of mobile telecommunication channels change rapidly, classical adaptive filters, such as exponentially weighted least squares algorithms or gradient algorithms, fail to estimate them with sufficient accuracy. In cases like this, one can use identification methods based on explicit models of parameter changes such as the method of basis functions (BF). When prior knowledge about parameter changes is available the...
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M-integral for finite anti-plane shear of a nonlinear elastic matrix with rigid inclusions
PublicationThe path-independent M-integral plays an important role in analysis of solids with inhomogeneities. However, the available applications are almost limited to linear-elastic or physically non-linear power law type materials under the assumption of infinitesimal strains. In this paper we formulate the M-integral for a class of hyperelastic solids undergoing finite anti-plane shear deformation. As an application we consider the problem...
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A variational approach of homogenization of piezoelectric composites towards piezoelectric and flexoelectric effective media
PublicationThe effective piezoelectric properties of heterogeneous materials are evaluated in the context of periodic homogenization, whereby a variational formulation is developed, articulated with the extended Hill macrohomogeneity condition. The entire set of homogenized piezoelectric moduli is obtained as the volumetric averages of the microscopic properties of the individual constituents weighted by the displacement and polarization...
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Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublicationWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Electronic Noses and Electronic Tongues
PublicationChapter 7 reports the achievements on the field of artificial senses, such as electronic nose and electronic tongue. It examines multivariate data processing methods and demonstrates a promising potential for rapid routine analysis. Main attention is focused on detailed description of sensor used, construction and principle of operation of these systems. A brief review about the progress in the field of artificial senses and future trends...
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Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
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Asynchronous phase-location system
PublicationThis paper presents concept and implementation of digital phase-location system, designed as a navigational aid for marine applications. The main feature of the proposed system is the ability to work in both synchronous mode, with one master station and set of slave stations synchronised with master, and in asynchronous mode with independent clocking of all stations.
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Digital phase-location system for marine applications
PublicationThis paper presents concept and implementation of digital phase-location system, designed as a navigational aid for marine applications. Main feature of proposed system is the ability to work in both synchronous mode, with one master station and set of slave stations synchronized with master, and in asynchronous mode with independent clocking of all stations.
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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublicationIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublicationIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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EPILEPTIC BEHAVIOR WITH A DISTINGUISHED PREICTAL PERIOD IN A LARGE-SCALE NEURAL NETWORK MODEL
PublicationWe present a neural network model capable of reproducing focal epileptic behavior. An important property of our model is the distinguished preictal state. This novel feature may shed light on the pathologi-cal mechanisms of seizure generation and, in perspective, help develop new therapeutic strategies to manage refractory partial epilepsy.
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The safety issue of roadside advertising – comparison of polish and abu dhabi regulations
PublicationIn Poland a large number of advertisements are located by the roadside. These ads do not support road traffic management and unlike the road marking system are not subject to any regulations. The advertiser’s goal is to communicate a message to as many recipients as possible. Drivers with different individual abilities, such as attention focusing, eye accommodation, speed of information processing, can be distracted, blinded or...
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Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery
Publication"Generalized Continual Category Discovery (GCCD) tackles learning from sequentially arriving, partially labeled datasets while uncovering new categories. Traditional methods depend on feature distillation to prevent forgetting the old knowledge. However, this strategy restricts the model’s ability to adapt and effectively distinguish new categories. To address this, we introduce a novel technique integrating a learnable projector...
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Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...