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Search results for: support vector regressor
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A new concept of PWM duty cycle computation using the Barycentric Coordinates in a Three-Dimensional voltage vectors arrangement
PublicationThe paper presents a novel approach to the Pulse Width Modulation (PWM) duty cycle computing for complex or irregular voltage vector arrangements in the two (2D) and three–dimensional (3D) Cartesian coordinate systems. The given vectors arrangement can be built using at least three vectors or collections with variable number of involved vectors (i.e. virtual vectors). Graphically, these vectors form a convex figure, in particular,...
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Double Fed Induction Machine Drives
PublicationContents of the Chapter 22:Machine model.Properties of the DFM.Steady state machine operation.Control rules and decoupled control.Decoupling based on MM machine model.Decoupling based on vector model.Decoupling based on rotor current equation.Overall control system.Control system based on MM model.Control system based on vector model.Estimation of variables.Calculation of the angle between stator and rotor.Remarks about digital...
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings
PublicationTraffic-induced vibrations may cause various damages to buildings located near the road, including cracking of plaster, cracks in load-bearing elements or even collapse of the whole structure. Measurements of vibrations of real buildings are costly and laborious. Therefore the aim of the research is to propose the original numerical algorithm which allows us to predict, with high probability, the nega-tive dynamic impact of traffic-induced...
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Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
PublicationThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including:...
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Automatic labeling of traffic sound recordings using autoencoder-derived features
PublicationAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
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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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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublicationLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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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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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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Improved RSS-Based DoA Estimation Accuracy in Low-Profile ESPAR Antenna Using SVM Approach
PublicationIn this paper, we have shown how the overall performance of direction-of-arrival (DoA) estimation using lowprofile electronically steerable parasitic array radiator (ESPAR) antenna, which has been proposed for Internet of Things (IoT) applications, can significantly be improved when support vector machine (SVM) approach is applied. Because the SVM-based DoA estimation method used herein relies solely...
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Analiza stanu nawierzchni i klas pojazdów na podstawie parametrów ekstrahowanych z sygnału fonicznego
PublicationCelem badań jest poszukiwanie parametrów wektora cech ekstrahowanego z sygnału fonicznego w kontekście automatycznego rozpoznawania stanu nawierzchni jezdni oraz typu pojazdów. W pierwszej kolejności przedstawiono wpływ warunków pogodowych na charakterystykę widmową sygnału fonicznego rejestrowanego przy przejeżdżających pojazdach. Następnie, dokonano parametryzacji sygnału fonicznego oraz przeprowadzano analizę korelacyjną w celu...
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The Influence of Selecting Regions from Endoscopic Video Frames on The Efficiency of Large Bowel Disease Recognition Algorithms
PublicationThe article presents our research in the field of the automatic diagnosis of large intestine diseases on endoscopic video. It focuses on the methods of selecting regions of interest from endoscopic video frames for further analysis by specialized disease recognition algorithms. Four methods of selecting regions of interest have been discussed: a. trivial, b. with the deletion of characteristic, endoscope specific additions to the...
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Multiparameter sensitivity analysis of a GFRP composite footbridge of a sandwich structure and U-shaped cross-section
PublicationThe paper deals with multiparameter sensitivity analysis of a composite footbridge. A shell‐like structure is 14.5 m long shows U‐shaped cross‐section and inner service dimensions 1.3 × 2.5 m. Glass fiber reinforced polymer GFRP laminate constitutes faces of a sandwich structure while PET foam received from recycled bottle builts a core. The structure was divided into 285 independent areas where the thickness of laminates and stiffness...
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Towards Rational Biosurfactant Design—Predicting Solubilization in Rhamnolipid Solutions
PublicationThe efficiency of micellar solubilization is dictated inter alia by the properties of the solubilizate, the type of surfactant, and environmental conditions of the process. We, therefore, hypothesized that using the descriptors of the aforementioned features we can predict the solubilization efficiency, expressed as molar solubilization ratio (MSR). In other words, we aimed at creating a model to find the optimal surfactant and...
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Digital transformation and economic growth - DESI improvement and implementation
PublicationThe paper aims to improve the methodology of the Digital Economic and Society Index (DESI), the European Commission’s newest index to assess the development of the digital economy. In particular, we investigate whether methodological changes to the structure of DESI improve its ability to capture the digital transformation of EU economies. Using the sensitivity- based analysis, we check whether the selection of weights of individual...
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Stability of trusses with linear elastic side-supports
PublicationThe present research is devoted to study of a lateral buckling of truss with linear elastic side supports. The elastic support reaction in relation to force in compressed chord and coefficient of buckling length related to side support distance are also calculated. The effect of slope of side support on limit force is also considered. The nonlinear analysis of two roof trusses are carried out. The results are compared to design...
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Multibody models for gait analysis
PublicationThe aim of this study was to create multibody biomechanical models to analyze a normal gait of the human. Proposed models can be used to identify joint moments of the lower limbs during normal gait in the single and double support phases. Applying Newton-Euler formulation, following planar models were developed: 1) a mathematical 6DOF model describing a gait in the sagittal plane of the body for single support phase and double...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams
PublicationA system for recognition of threatening acoustic events employing parallel processing on a supercomputing cluster is featured. The methods for detection, parameterization and classication of acoustic events are introduced. The recognition engine is based onthreshold-based detection with adaptive threshold and Support Vector Machine classifcation. Spectral, temporal and mel-frequency descriptors are used as signal features. The...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Feedback Control of Multiphase Induction Machines with Backstepping Technique
PublicationThe paper presents the control possibility of five phase induction machines. In the proposed solution the machine model vector form is not transformed to the (dq)-coordinate system, that is connected to rotor flux vector, but utilizes the stationary system ( αβ ). Moreover, the nonlinear model linearization is based on demonstrated nonlinear variables transformation for i-orthogonal ( αβ )(n) planes. By introducing the backstepping...
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Activation of the operational ecohydrodynamic model (3D CEMBS) – the ecosystem module**The study was supported by the Polish State Committee of Scientific Research (grants: N N305 111636, N N306 353239). Partial support was also provided by the Satellite Monitoring of the Baltic Sea Environment – the SatBałtyk project funded by the European Union through the European Regional Development Fund contract No. POIG 01.01.02-22-011/09.
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A System for Heart Sounds Classification
PublicationThe future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublicationWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
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Multicomponent ionic liquid CMC prediction
PublicationWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublicationThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
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MARKAL LONG-TERM POWER GENERATION SCENARIOS FOR POLAND: INCREASING THE SHARE OF RENEWABLE ENERGY SOURCES BY 2040
PublicationIn this paper, renewable energy sources (RES) support mechanisms in Poland was presented with perspectives of proposed support system modifications, discussed in the project of Renewable Energy Act. In addition, MARKAL model of RES support mechanism was presented, taking into account technology-specific multiplication factors. Two model runs with emission trading system in place and two additional runs without emission trade were...
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Hybridized PWM Strategy for Three- and Multiphase Three-Level NPC Inverters
PublicationA simple hybridized pulsewidth modulation (PWM) algorithm for three- and multiphase three-level neutral point clamped (NPC) inverters is proposed. The proposed solution is based on classical space vector PWM (SVPWM) algorithms for two-level inverters but can also be based on sinusoidal PWM with min–max injection. An additional level of output voltage is obtained by modifying the resulting switching patterns taking into account...
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MARKAL long-term power generation scenarios for Poland: Increasing the share of renewable energy sources by 2040
PublicationIn this paper, renewable energy sources (RES) support mechanisms in Poland was presented with perspec-tives of proposed support system modifications, discussed in the project of Renewable Energy Act. In ad-dition, MARKAL model of RES support mechanism was presented, taking into account technology-specific multiplication factors. Two model runs with emission trading system in place and two additional runs without emission trade...
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Comparative Analysis of Text Representation Methods Using Classification
PublicationIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Fundamentals of Data-Driven Surrogate Modeling
PublicationThe primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublicationHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Pathological and physiological high-frequency oscillations in focal human epilepsy
PublicationHigh-frequency oscillations (HFO; gamma: 40-100 Hz, ripples: 100-200 Hz, and fast ripples: 250-500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency,...
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Social media for e-learning of citizens in smart city
PublicationThe rapid development of social media can be applied for citizens’ e-learning in a smart city. Big cities have to cope with several open issues like a growing population or a traffic congestion. Especially, a home and public space is supposed to be used in more efficient way. Sustainable homes and buildings can be planned with using some modern techniques. Even currently, there is a huge problem with a lack of key resources like...
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Information retrieval with semantic memory model
PublicationPsycholinguistic theories of semantic memory form the basis of understanding of natural language concepts. These theories are used here as an inspiration for implementing a computational model of semantic memory in the form of semantic network. Combining this network with a vector-based object-relation-feature value representation of concepts that includes also weights for confidence and support, allows for recognition of concepts...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Morse cohomology in a Hilbert space via the Conley index
PublicationThe main theorem of this paper states that Morse cohomology groups in a Hilbert space are isomorphic to the cohomological Conley index. It is also shown that calculating the cohomological Conley index does not require finite-dimensional approximations of the vector field. Further directions are discussed.
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Detection and localization of selected acoustic events in acoustic field for smart surveillance applications
PublicationA method for automatic determination of position of chosen sound events such as speech signals and impulse sounds in 3-dimensional space is presented. The evens are localized in the presence of sound reflections employing acoustic vector sensors. Human voice and impulsive sounds are detected using adaptive detectors based on modified peak-valley difference (PVD) parameter and sound pressure level. Localization based on signals...
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Non-Adaptive Speed and Position Estimation of Doubly-Fed Induction Generator in Grid-Connected Operations
PublicationThe nonadaptive speed and position estimation scheme for a doubly-fed induction generator (DFIG) is presented in this article. The observer structure is based on the extension of the mathematical model of DFIG to the introduced H vector. Based on the defined H vector, the nonadaptive position and speed estimation is proposed. The Lyapunov method is extended to the practical stability theorem to stabilize the structure. The classic...
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Enhancing women’s engagement in economic activities through information and communication technology deployment: evidence from Central–Eastern European countries
PublicationThis study takes a macro perspective to examine the associations between the economic deployment of information and communication technology (ICT), women’s labor market participation, and economic growth in Central–Eastern European countries between 1990 and 2017. We use data extracted from World Bank Development Indicators, World Development Reports, and the World Telecommunication/ICT Indicators Database. Our methodological framework...
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Detection and localization of selected acoustic events in 3D acoustic field for smart surveillance applications
PublicationA method for automatic determination of position of chosen sound events such as speech signals and impulse sounds in 3-dimensional space is presented. The events are localized in the presence of sound reflections employing acoustic vector sensors. Human voice and impulsive sounds are detected using adaptive detectors based on modified peak-valley difference (PVD) parameter and sound pressure level. Localization based on signals...
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Supporting Management Decisions with Intelligent Mechanisms of Obtaining and Processing Knowledge
PublicationThis paper is a summary of the authors' work on a model of support for decision processes in organisation management. Key decisions in organisations are often made without sufficient knowledge and by people lacking the proper qualifications and experience. Without full support in decision processes, true threats to organisations are created. Therefore, to support decision processes in numerous organisations, apart from experts...
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Evaluation of Selected Innovation Policy Instruments on the Example of Poland
PublicationThe main purpose of the paper is to analyze and evaluate the selected instruments of innovation policy in Poland: cooperative relations, business environment institutions and innovation centers, supported within Priority Axis V of OP IE 2007-2013. The evaluation was made on the basis of the four criteria: complementarity, adapting to the needs of businesses, the impact on the innovation and durability of the provided support. The...
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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...