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Search results for: 2D FEATURE REPRESENTATIONS
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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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A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces
PublicationIn this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation...
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublicationDeveloping signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....
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Detecting Lombard Speech Using Deep Learning Approach
PublicationRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Design-oriented computationally-efficient feature-based surrogate modelling of multi-band antennas with nested kriging
PublicationDesign of modern antenna structures heavily depends on electromagnetic (EM) simulation tools. EM analysis provides reliable evaluation of increasingly complex designs but tends to be CPU intensive. When multiple simulations are needed (e.g., for parameters tuning), the aggregated simulation cost may become a serious bottleneck. As one possible way of mitigating the issue, the recent literature fosters utilization of faster representations,...
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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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2D Mathematical Model of the Commutator Sliding Contact of an Electrical Machine
PublicationW artykule przedstawiono model matematyczny 2D komutatorowego zestyku ślizgowego z wieloma stopniami swobody. W modelu uwzględniono zmienne wymuszenia działające na szczotkę. Wymuszenia te są wynikiem falistości wirującego komutatora. Szczotka została zamodelowana jako system wielu mas, elementów sprężystych i tłumików rozłożonych w kierunku stycznym i promieniowym. Zamodelowano wszystkie oddziaływania lepkosprężyste pomiędzy komutatorem...
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Analysis-by-synthesis paradigm evolved into a new concept
PublicationThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
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Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublicationThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Embedded Representations of Wikipedia Categories
PublicationIn this paper, we present an approach to building neural representations of the Wikipedia category graph. We test four different methods and examine the neural embeddings in terms of preservation of graphs edges, neighborhood coverage in representation space, and their influence on the results of a task predicting parent of two categories. The main contribution of this paper is application of neural representations for improving the...
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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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Reduced-Cost Two-Level Surrogate Antenna Modeling using Domain Confinement and Response Features
PublicationElectromagnetic (EM) simulation tools have become indispensable in the design of contemporary antennas. Still, the major setback of EM-driven design is the associated computational overhead. This is because a single full-wave simulation may take from dozens of seconds up to several hours, thus, the cost of solving design tasks that involve multiple EM analyses may turn unmanageable. This is where faster system representations (surrogates)...
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A Quasi-2D MOSFET Model — 2D-to-Quasi-2D Transformation
PublicationA quasi-two-dimensional (quasi-2D) representation of the MOSFET channel is proposed in this work. The representation lays the foundations for a quasi 2D MOSFET model. The quasi 2D model is a result of a 2D into quasi 2D transformation. The basis for the transformation are an analysis of a current density vector field and such phenomena as Gradual Channel Detachment Effect (GCDE), Channel Thickness Modulation Effect (CTME), and...
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Representations
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A comparison of geometric analogues of holographic reduced representations, original holographic reduced representations and binary spatter codes
PublicationGeometric Analogues of Holographic Reduced Representations (GA HRR) employ role-filler binding based on geometric products. Atomic objects are real-valued vectors in n-dimensional Euclidean space and complex statements belong to a hierarchy of multivectors. The paper reports a battery of tests aimed at comparison of GA HRR with Holographic Reduced Representation (HRR) and Binary Spatter Codes (BSC). Firstly, we perform a test of...
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Geometric Algebra Model of Distributed Representations
PublicationFormalism based on GA is an alternative to distributed representation models developed so far-Smolensky's tensor product, Holographic Reduced Representations (HRR) and Binary Spatter Code (BSC). Convolutions are replaced by geometric products, interpretable in terms of geometry which seems to be the most natural language for visualization of higher concepts. This paper recalls the main ideas behind the GA model and investigates...
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An insight into the mixed quantum mechanical-molecular dynamics simulation of a ZnII-Curcumin complex with a chosen DNA sequence that supports experimental DNA binding investigations
PublicationAn important aspect of research pertaining to Curcumin (HCur) is the need to arrest its degradation in aqueous solution and in biological milieu. This may be achieved through complex formation with metal ions. For this reason, a complex of HCur was prepared with ZnII, that is not likely to be active in redox pathways, minimizing further complications. The complex is monomeric, tetrahedral, with one HCur, an acetate and a molecule...
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2D Materials
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries
PublicationLocalizing instrument parts in video-assisted surgeries is an attractive and open computer vision problem. A working algorithm would immediately find applications in computer-aided interventions in the operating theater. Knowing the location of tool parts could help virtually augment visual faculty of surgeons, assess skills of novice surgeons, and increase autonomy of surgical robots. A surgical tool varies in appearance due to...
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Jumping Wave 2D Profiles
Open Research DataThe file contains 2D profiles obtained from a jumping wave study in front of the tool during burnishing of 1.0562 steel by the toroidal-cone tool. Burnishing speed 30.5 m/min, feed of burnishing 0.2mm/rev Force 550 and 800 N.
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2D inverse method of turbomachinery stage design
Publication1. How 2D model for turbomachinery stages has developed historically. 2. Recent understanding of physical background of 2D model. 3. Curvilinear system of non-orthogonal coordinates in the application to 2D model. 4. Set of basic equations. 5. Closing conditions for the inverse problem. 6. Examples of solutions a)
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Investigating Feature Spaces for Isolated Word Recognition
PublicationMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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Investigating Feature Spaces for Isolated Word Recognition
PublicationThe study addresses the issues related to the appropriateness of a two-dimensional representation of speech signal for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and...
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Regularization as quantization in reducible representations of CCR
PublicationOpis kwantowego pola elektromagnetycznego przy pomocy redukowalnych reprezentacji CCR prowadzi do automatycznej regularyzacji teorii. Sformułowanie jest jawnie relatywistycznie współzmiennicze. Przeanalizowano - jako przykład - pola kwantowe wytwarzane przez klasyczne źródła.
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Spin and Orbital Effects on Asymmetric Exchange Interaction in Polar Magnets: M(IO3)2 (M = Cu and Mn)
PublicationMagnetic polar materials feature an astonishing range of physical properties, such as magnetoelectric coupling, chiral spin textures, and related new spin topology physics. This is primarily attributable to their lack of space inversion symmetry in conjunction with unpaired electrons, potentially facilitating an asymmetric Dzyaloshinskii–Moriya (DM) exchange interaction supported by spin–orbital and electron–lattice coupling. However,...
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Facial feature extraction from a monochromatic picture.
PublicationFace pose determination represents an important area of research in Human Machine Interaction. In this paper, I describe a new method of extracting facial feature locations from a single monochromatic monocular camera for the purpose of estimating and tracking the three dimensional pose of human face and eye-gaze direction.
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Facial Feature extraction from a monochromatic picture
PublicationFace pose determination represents an important area of research in Human Machine Interaction. In this paper, I describe a new method of extracting facial feature locations from a single monochromatic monocular camera for the purpose of estimating and tracking the three dimensional pose of human face and eye-gaze direction.
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Reduced order model of 2d system
PublicationA new method of modelling is developed for static and dynamic analysis of two-dimensional elastic bodies. In the analysis, an elastic body is divided into strips. For each one-dimensional strip the reduced modal model is build up. The modal model contains appropriate number of inputs and outputs to connect lumped interaction that occur between strips. Proposed method of modelling enables to obtain more accurate and more simple...
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Papers on Social Representations
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Societes et Representations
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2D MXene nanocomposites: electrochemical and biomedical applications
PublicationIn recent years, key questions about the interaction of 2D MXene nanomaterials in electrochemical and biomedical applications have been raised. Most research has focused on clarifying the exclusive properties of the materials; however, only limited reports have described the biomedical applications of 2D nanomaterials. 2D MXenes are monolayer atomic nanosheets resulting from MAX phase ceramics. The hydrophilic properties, metallic...
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Using similar classification tasks in feature extractor learning
PublicationThe article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.
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Synthesis, characterization, and application of 2D/2D TiO2-GO-ZnFe2O4 obtained by the fluorine-free lyophilization method for solar light-driven photocatalytic degradation of ibuprofen
PublicationIn this study, we report the potential of 2D/2D TiO2- GO-ZnFe2O4 photocatalyst obtained using the fluorine-free lyophilization technique for the degradation of ibuprofen belonging to the group of active pharmaceutical ingredients (API). The improved ibuprofen degradation under simulated solar light was achieved in the presence of a composite of 2D TiO2 combined with GO and embedded ZnFe2O4, which additionally provides superparamagnetic...
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Flow models 1D, 2D, 3D for diagonal pump
PublicationTrzy typowe modele stosowane w maszynach wirnikowych 1D, 2D, 3D zostały przedstawione w zastosowaniu do przepływu w pompie diagonalnej. W ramach modelu 1D przedstawiono prezentację procesu na wykresie energia -straty. W ramach modelu 2D pokazano wynik rozwiązania zadania odwrotnego prowadzącego do kształtu łopatek wirnika pompy. W ramach modelu 3D wykonano obliczenia programem FLUENT pokazując charakterystyczne cechy dwóch różnie...
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Experiments on Preserving Pieces of Information in a Given Order in Holographic Reduced Representations and the Continuous Geometric Algebra Model
PublicationGeometric Analogues of Holographic Reduced Representations (GAc, which is the continuous version of the previously developed discrete GA model) employ role-filler binding based on geometric products.Atomic objects are real-valued vectors in n-dimensional Euclidean space and complex statements belong to a hierarchy of multivectors. The property of GAc and HRR studied here is the ability to store pieces of information in a given...
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Automatic Regularization by Quantization in Reducible Representations of CCR: Point-Form Quantum Optics with Classical Sources
PublicationElectromagnetic fields are quantized in a manifestly covariant way by means ofa class of reducible "center-of-mass N-representations" of the algebra of canonical commutationrelations (CCR). The four-potential Aa(x) transforms in these representations as aHermitian four-vector field in Minkowski four-position space (without change of gauge), butin momentum space it splits into spin-1 massless photons and two massless scalars. Whatwe...
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Distributed Representations Based on Geometric Algebra: the Continuous Model
PublicationAuthors revise the concept of a distributed representation of data as well as two previously developed models: Holographic Reduced Representation (HRR) and Binary Spatter Codes (BSC). A Geometric Analogue (GAc - ''c'' stands for continuous as opposed to its discrete version) of HRR is introduced - it employs role-filler binding based on geometric products. Atomic objects are real-valued vectors in n-dimensional Euclidean space...
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Identity verification using complex representations of handwritten signature
PublicationThis paper is devoted to handwritten signature verification using the cross-correlation approach (adopted by the authors from telecommunications) and dynamic time warping. The following invariants of the handwritten signature: the net signature, the instantaneous complex frequency and the complex cepstrum are analyzed. The problem of setting the threshold for deciding whether the current signature is authentic or forged is discussed....
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A quasi-2D small-signal MOSFET model - main results
PublicationMain results stemming from a new quasi 2D non-quasi-static small-signal four-terminal model of the MOSFET are presented in this work. The model is experimentally verified up to 30 GHz.
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TIME- AND FREQUENCY-DOMAIN QUASI-2D SMALL-SIGNAL MOSFET MODELS
PublicationA novel approach to small-signal MOSFET modeling is presented in this book. As a result, time- and frequency-domain physics-based quasi-2D NQS four-terminal small-signal MOSFET models are proposed. The time-domain model provides the background to a novel DIBL-included quasi‑2D NQS four-terminal frequency-domain small-signal MOSFET model. Parameters and electrical quantities of the frequency-domain model are described by explicit...
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IMPEDANCE MEASUREMENT MODULE FOR GAS SENSORS WITH TEMPERATURE CONDITIONING FEATURE
PublicationThe paper presents an impedance measurement module which is aimed for gas sensor. Sensor’s heater temperature conditioning and modulation feature is available in order to allow implementation of different techniques improving selectivity and sensitivity of gas sensors. The measurement module uses three-parameter sine-fitting technique for impedance measurement. To monitor sensor temperature, the resistance of the sensor’s heater...
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Low-Level Music Feature Vectors Embedded as Watermarks
PublicationIn this paper a method consisting in embedding low-level music feature vectors as watermarks into a musical signal is proposed. First, a review of some recent watermarking techniques and the main goals of development of digital watermarking research are provided. Then, a short overview of parameterization employed in the area of Music Information Retrieval is given. A methodology of non-blind watermarking applied to music-content...
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A quasi-2D small-signal MOSFET model - main results
PublicationDynamic properties of the MOS transistor under small-signal excitation are determined by kinetic parameters of the carriers injected into the channel, i.e., the low-field mobility, velocity saturation, mobility at the quiescent-point (Q-point), longitudinal electric field in the channel, by dynamic properties of the channel, as well as by an electrical coupling between the perturbed carrier concentration in the channel and the...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Response Feature Technology for High-Frequency Electronics. Optimization, Modeling, and Design Automation
PublicationThis book discusses response feature technology and its applications to modeling, optimization, and computer-aided design of high-frequency structures including antenna and microwave components. By exploring the specific structure of the system outputs, feature-based approaches facilitate simulation-driven design procedures, both in terms of improving their computational efficiency and reliability. These benefits are associated...
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Real-time facial feature tracking in poor quality thermal imagery
PublicationRecently, facial feature tracking systems have become more and more popular because of many possible use cases. Especially in medical applications location of the face and facial features are very useful. Many researches have presented methods to detect and track facial features in visible light. However, facial feature analysis in thermography may also be very advantageous. Some examples of using infrared imagery in medicine include...
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Influence of mesh density on 2D viscous flutter in a turbomachinery cascade
PublicationIn this study numerical simulations of 2D viscous flutter were performed and compared with available experimental results for various mesh densities and flow parameters. Calculations were carried out for the bending oscillations of an Eleventh Standard Configuration cascade. ANSYS CFX code was used for the SST, SA and k-ω turbulence model calculations.