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Search results for: NEURAL TEXT-TO-SPEECH MULTILINGUAL SYNTHESIS VOICE CONVERSION SYNTHETIC DATA NORMALISING FLOWS
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Literary Voice
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Synthetic Biology
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Coal Conversion
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Early Stages of RNA-Mediated Conversion of Human Prions
PublicationPrion diseases are characterized by the conversion of prion proteins from a PrPC fold into a disease-causing PrPSC form that is self-replicating. A possible agent to trigger this conversion is polyadenosine RNA, but both mechanism and pathways of the conversion are poorly understood. Using coarse-grained molecular dynamic simulations we study the time evolution of PrPC over 600 μs. We find that both the D178N mutation and interacting...
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Decoding imagined speech for EEG-based BCI
PublicationBrain–computer interfaces (BCIs) are systems that transform the brain's electrical activity into commands to control a device. To create a BCI, it is necessary to establish the relationship between a certain stimulus, internal or external, and the brain activity it provokes. A common approach in BCIs is motor imagery, which involves imagining limb movement. Unfortunately, this approach allows few commands. As an alternative, this...
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Variational Method of Finding Streamlines in Ring Cascades for Creeping Flows
PublicationThis paper presents a new, analytical method of finding streamlinesfor creeping flows inside a ring cascade which is composed of an infinite number of infinitely thin blades. An analytical solution has been obtained through minimisation of a dissipation functional by means of variational calculus method. The necessary condition for optimum of a functional gives the Stokes equation if some additional assumptions are introduced....
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Understanding Knowledge-Intensive Business Services. Identification, Systematization, and Characterization of Knowledge Flows
PublicationThis book contributes to an improved understanding of knowledge-intensive business services and knowledge management issues. It offers a complex overview of literature devoted to these topics and introduces the concept of ‘knowledge flows’, which constitutes a missing link in the previous knowledge management theories. The book provides a detailed analysis of knowledge flows, with their types, relations and factors influencing...
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Two Stage SVM and kNN Text Documents Classifier
PublicationThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Neural Modelling of Steam Turbine Control Stage
PublicationThe paper describes possibility of steam turbine control stage neural model creation. It is of great importance because wider application of green energy causes severe conditions for control of energy generation systems operation Results of chosen steam turbine of 200 MW power measurements are applied as an example showing way of neural model creation. They serve as training and testing data of such neural model. Relatively simple...
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Review: synthetic polymer hydrogels for biomedical applications
PublicationSynthetic polymer hydrogels constitute a group of biomaterials, used in numerous biomedical disciplines, and are still developing for new promising applications. The aim of this study is to review information about well known and the newest hydrogels, show the importance of water uptake and cross-linking type and classify them in accordance with their chemical structure.
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Towards Effective Processing of Large Text Collections
PublicationIn the article we describe the approach to parallelimplementation of elementary operations for textual data categorization.In the experiments we evaluate parallel computations ofsimilarity matrices and k-means algorithm. The test datasets havebeen prepared as graphs created from Wikipedia articles relatedwith links. When we create the clustering data packages, wecompute pairs of eigenvectors and eigenvalues for visualizationsof...
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System Supporting Speech Perception in Special Educational Needs Schoolchildren
PublicationThe system supporting speech perception during the classes is presented in the paper. The system is a combination of portable device, which enables real-time speech stretching, with the workstation designed in order to perform hearing tests. System was designed to help children suffering from Central Auditory Processing Disorders.
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Client-side versus server-side geographic data processing performance comparison: Data and code
PublicationThe data and code presented in this article are related to the research article entitled “Analysis of Server-side and Client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and Geoportal” (Kulawiak et al., 2019). The provided 12 datasets include multi-point and multi-polygon data of different scales and volumes, representing real-world geographic features. The datasets cover the area...
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Silence/noise detection for speech and music signals
PublicationThis paper introduces a novel off-line algorithm for silence/noise detection in noisy signals. The main concept of the proposed algorithm is to provide noise patterns for further signals processing i.e. noise reduction for speech enhancement. The algorithm is based on frequency domain characteristics of signals. The examples of different types of noisy signals are presented.
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Analysis of Lombard speech using parameterization and the objective quality indicators in noise conditions
PublicationThe aim of the work is to analyze Lombard speech effect in recordings and then modify the speech signal in order to obtain an increase in the improvement of objective speech quality indicators after mixing the useful signal with noise or with an interfering signal. The modifications made to the signal are based on the characteristics of the Lombard speech, and in particular on the effect of increasing the fundamental frequency...
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Thresholding Strategies for Large Scale Multi-Label Text Classifier
PublicationThis article presents an overview of thresholding methods for labeling objects given a list of candidate classes’ scores. These methods are essential to multi-label classification tasks, especially when there are a lot of classes which are organized in a hierarchy. Presented techniques are evaluated using the state-of-the-art dedicated classifier on medium scale text corpora extracted from Wikipedia. Obtained results show that the...
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Temperature, velocity and mean turbulence structure in strongly heated internal gas flows. Comparison of numerical predictions with data
PublicationW pracy przedstawiono symulacje numeryczne przy użyciu szeregu modeli turbulencji celem analizy silnie ogrzewanego przepływu powietrza w pionowych rurach. Obliczenia porównano z danymi eksperymentalnymi. Analizowano modyfikacje pola prędkości, temperatury i turbulencji. W rozpatrywanych warunkach odnotowano silną wrażliwość obliczeń na silnie zmieniające się pole temperatury. Stwierdzono, że analizowane przypadki najlepiej odzwierciedla...
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Parallel Computations of Text Similarities for Categorization Task
PublicationIn this chapter we describe the approach to parallel implementation of similarities in high dimensional spaces. The similarities computation have been used for textual data categorization. A test datasets we create from Wikipedia articles that with their hyper references formed a graph used in our experiments. The similarities based on Euclidean distance and Cosine measure have been used to process the data using k-means algorithm....
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Text-mining Similarity Approximation Operators for Opinion Mining in BI tools
PublicationThe concept of the Text-mining Similarity Approximation Operators for Opinion Mining as extensions to Natural Language Interface Database is defined. The new operators: “keywords of” dimension; subsetting operator “about C is q”; aggregation operator “by similar C” are proposed. These operators are based on the Latent Semantic Analysis and Social Network Analysis
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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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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Neural networks and deep learning
PublicationIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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Calculations of Short-Circuit Current Flows in Earth Wires of HV Lines
PublicationThis paper presents a method which enables calculating flows of short-circuit currents in earth wires of high voltage transmission lines, and its implementation in the form of a computer programme. The algorithm enables performing calculations for a double-fed line and starconnected lines (three terminal lines). The developed programme enables verifying dimensioning of earth wires in the context of their short-circuit thermal withstand...
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Corrupted speech intelligibility improvement using adaptive filter based algorithm
PublicationA technique for improving the quality of speech signals recorded in strong noise is presented. The proposed algorithmemploying adaptive filtration is described and additional possibilities of speech intelligibility improvement arediscussed. Results of the tests are presented.
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Intra-subject class-incremental deep learning approach for EEG-based imagined speech recognition
PublicationBrain–computer interfaces (BCIs) aim to decode brain signals and transform them into commands for device operation. The present study aimed to decode the brain activity during imagined speech. The BCI must identify imagined words within a given vocabulary and thus perform the requested action. A possible scenario when using this approach is the gradual addition of new words to the vocabulary using incremental learning methods....
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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Ag modified ZnO microsphere synthesis for efficient sonophotocatalytic degradation of organic pollutants and CO2 conversion
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Automatic classification of singing voice quality
PublicationW artykule przedstawiono zagadnienia związane z automatyczną klasyfikacją jakości i rodzajów głosów śpiewaczych. Na potrzebę takiej klasyfikacji stworzono bazę głosów śpiewaczych, w której dokonano parametryzacji nagrań samogłosech śpiewanych przez różnych wokalistów (zarówno profesjonalistów jak i amatorów) na różnych wysokościach i z różną głośnością. W celu ograniczenia wymiaru wektora opisu zastosowano statystykę Behrensa Fishera...
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A Convenient Synthesis of Monocationic 1-[(Cyclic amidino)methyl]thymines
Publication1-[(Cyclic amidino)methyl]thymines have been conveniently synthesized from thymine in a three-step procedure via 1-cyanomethyl- and 1-[(thiocarbamoyl) methyl]thymines. The above synthetic intermediates were obtained in good yields by improved methods.
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Novel and Efficient Methods for the Synthesis of Symmetrical Trisulfides
PublicationWe have developed a convenient methods for the synthesis of symmetrical trisulfides under mild conditions in very good yields. The described methods are based on the straightforward preparation of 5,5-dimethyl-2-thioxo-1,3,2-dioxaphosphorinane-2-disulfanyl derivatives from readily available 5,5-dimethyl-2-sulfanyl-2-thioxo-1,3,2-dioxaphosphorinane or bis(5,5-dimethyl-2-thioxo-1,3,2-dioxaphosphorinan-2-yl) disulfide. The symmetrical...
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Anna Zielińska-Jurek prof. dr hab. inż.
People2018 DSc in technical sciences in the field of chemical technology Chemical Faculty, Gdansk University of Technology, Title: “Functionalized titanium(IV) oxide as a photocatalyst for environmental purification” 2011 Ph. D. in technical sciences in the field of chemical technology Chemical Faculty, Gdansk University of Technology, Title of the dissertation:...
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Synthesis philosophica
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Synthesis, Bucuresti
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Text Mining Algorithms for Extracting Brand Knowledge; The fashion Industry Case
PublicationBrand knowledge is determined by customer knowledge. The opportunity to develop brands based on customer knowledge management has never been greater. Social media as a set of leading communication platforms enable peer to peer interplays between customers and brands. A large stream of such interactions is a great source of information which, when thoroughly analyzed, can become a source of innovation and lead to competitive advantage....
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Electrochemically Induced Synthesis of Triphenylamine-based Polyhydrazones
PublicationTriphenylamine-based hydrazones were subjected to electropolymerization process that gave well conductive hydrazone based polymers. The first example of polyhydrazone formation during the electrochemical process was shown. The estimation of polymer structure was demonstrated using IR spectroelectrochemistry. The EPR spectroelectrochemistry allowed to explain why in some cases dimer couldn’t be formed. The results of electrochemical,...
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Bimodal classification of English allophones employing acoustic speech signal and facial motion capture
PublicationA method for automatic transcription of English speech into International Phonetic Alphabet (IPA) system is developed and studied. The principal objective of the study is to evaluate to what extent the visual data related to lip reading can enhance recognition accuracy of the transcription of English consonantal and vocalic allophones. To this end, motion capture markers were placed on the faces of seven speakers to obtain lip...
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Journal of Computational Multiphase Flows
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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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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Building Knowledge for the Purpose of Lip Speech Identification
PublicationConsecutive stages of building knowledge for automatic lip speech identification are shown in this study. The main objective is to prepare audio-visual material for phonetic analysis and transcription. First, approximately 260 sentences of natural English were prepared taking into account the frequencies of occurrence of all English phonemes. Five native speakers from different countries read the selected sentences in front of...
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Transfer learning in imagined speech EEG-based BCIs
PublicationThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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Biomass Conversion and Biorefinery
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Sample Rate Conversion with Fluctuating Resampling Ratio
PublicationIn this paper a sample rate conversion with continuouslychanging resampling ratio has been presented. The proposed implementation is based on variable fractional delay filter implemented using a Farrow structure. It have been demonstrated that using the proposed approach instantaneous resampling ratio can be freely changed. This allows for simulation of audio recored on magnetic tape with nonuniform velocity as well as removal...
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A survey of neural networks usage for intrusion detection systems
PublicationIn recent years, advancements in the field of the artificial intelligence (AI) gained a huge momentum due to the worldwide appliance of this technology by the industry. One of the crucial areas of AI are neural networks (NN), which enable commer‐ cial utilization of functionalities previously not accessible by usage of computers. Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested...
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublicationIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Sample Rate Conversion with Fluctuating Resampling Ratio
PublicationIn this paper a sample rate conversion with continuously changing resampling ratio has been presented. The proposed implementation is based on variable fractional delay filter implemented using a Farrow structure. It have been demonstrated that using the proposed approach instantaneous resampling ratio can be freely changed. This allows for simulation of audio recored on magnetic tape with nonuniform velocity as well as removal...
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Enabling Deeper Linguistic-based Text Analytics – Construct Development for the Criticality of Negative Service Experience
PublicationSignificant progress has been made in linguistic-based text analytics particularly with the increasing availability of data and deep learning computational models for more accurate opinion analysis and domain-specific entity recognition. In understanding customer service experience from texts, analysis of sentiments associated with different stages of the service lifecycle is a useful starting point. However, when richer insights...
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Data governance: Organizing data for trustworthy Artificial Intelligence
PublicationThe rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements....