Словотвірний потенціал префіксальних дієслів зі значенням «переміщення вгору» в українській і польській мовах (зіставно-типологічний аспект)

The Derivational Potential of Prefixed Verbs with the Meaning of ‘Moving Upwards’ in the Ukrainian and Polish Languages (Comparative and Typological Aspects) This article is devoted to the derivational potential of prefixed verbs with the meaning ‘moving upwards’ in the Ukrainian and Polish languages in comparative and typological aspects. The study identifies the main factors that affect the derivational behaviour of the verbs in focus, delineates the structural types of specific derivational paradigms according to the number of word-class blocks of the deverbatives, reconstructs a typical derivational paradigm of the verbs under study, pinpoints the derivational meanings which fill this paradigm, and determines the ways of realisation of derivational meaning. The study found that prefixed verbs have a significant derivational potential. Based on a comparative analysis of derivational paradigms, it was established how prefixed verbs with the meaning of ‘moving upwards’ in the Ukrainian and Polish languages realise their derivational potential according to the following parameters: (1) the word-formative potential of the same lexical-semantic group to generate derivatives which belong to various blocks; (2) the derivational meanings of a typical derivational paradigm realised by derivatives in each of the compared languages; (3) the statistical pattern of derivational paradigm; (4) the degree of correspondence of the derivative potential of equivalent root words in the studied group; (5) correlate sets of derivational formants which are involved in the realisation of derivational meanings in a typical derivational paradigm; (6) the ways of formation of deverbatives in each of the languages, which reveals both common features and differences between them. Potencjał słowotwórczy czasowników przedrostkowych o znaczeniu ‘przemieszczać ku górze’ w języku ukraińskim i polskim (aspekt porównawczy i typologiczny) Artykuł skupia się na potencjale słowotwórczym czasowników przedrost­kowych o znaczeniu ‘przemieszczać ku górze’ w języku ukraińskim i polskim w aspekcie porównawczym i typologicznym. W toku badań ustalono główne czynniki wpływające na zachowanie słowotwórcze analizowanych czasowników, wyodrębniono typy strukturalne konkretnych paradygmatów słowotwórczych w zależności od liczby bloków części mowy, do jakich należą dewerbatywy, zrekonstruowano typowy paradygmat słowotwórczy analizowanych czasow­ników, wskazano znaczenia słowotwórcze, które wypełniają ten paradygmat, oraz określono sposoby realizacji znaczenia słowotwórczego. Badania wyka­zały, że czasowniki przedrostkowe mają znaczący potencjał słowotwórczy. Na podstawie analizy porównawczej paradygmatów słowotwórczych ustalono, w jaki sposób czasowniki przedrostkowe o znaczeniu ‘przemieszczać ku górze’ w języku ukraińskim i polskim realizują swój potencjał słowotwórczy według następujących parametrów: (1) potencjał słowotwórczy tej samej grupy leksykalno-semantycznej do generowania derywatów należących do różnych bloków; (2) znaczenia słowotwórcze typowego paradygmatu derywacyjnego, realizowane przez derywaty w porównywanych językach; (3) statystyczny schemat paradygmatu derywacyjnego; (4) stopień zgodności potencjału słowo­twórczego ekwiwalentów słów podstawowych w badanej grupie czasowników; (5) powiązane zbiory formantów derywacyjnych funkcjonujące w realizacji znaczeń w typowym paradygmacie słowotwórczym; (6) sposoby formowania dewerbatywów w porównywanych językach, ujawniające zarówno wspólne cechy, jak i różnice między nimi.

Voice Pathologies Classification Using GMM And SVM Classifiers

In this paper we investigate the proprieties of automatic speaker recognition (ASR) to develop a system for voice pathologies detection, where the model does not correspond to a speaker but it corresponds to group of patients who shares the same diagnostic. One of essential part in this topic is the database (described later), the samples voices (healthy and pathological) are chosen from a German database which contains many diseases, spasmodic dysphonia is proposed for this study. This problematic can be solved by statistical pattern recognition techniques where we have proposed the mel frequency cepstral coefficients (MFCC) to be modeled first, with gaussian mixture model (GMM) massively used in ASR then, they are modeled with support vector machine (SVM). The obtained results are compared in order to evaluate the more preferment classifier. The performance of each method is evaluated in a term of the accuracy, sensitivity, specificity. The best performance is obtained with 12 coefficientsMFCC, energy and second derivate along SVM with a polynomial kernel function, the classification rate is 90% for normal class and 93% for pathological class.This work is developed under MATLAB

Static strain-based identification of extensive damages in thin-walled structures

Interest has been expressed during the past few years toward incorporating structural health monitoring (SHM) systems in ship hull structures for detecting damages that cause significant load-carrying reductions and subsequent load redistributions. The guiding principle of the damage identification strategy considered in this work is based upon measuring, through a limited number of sensors, the static strain redistributions caused by an extensive damage. The problem is tackled as a statistical pattern recognition one, and therefore, methods sourcing from machine learning (ML) are applied. The SHM strategy is both virtually and experimentally applied to a thin-walled prismatic geometry that represents an idealized hull form solely subjected to principal bending stresses (sagging/hogging). Damage modes causing extensive stress redistribution, are abstractly represented by a circular discontinuity. The damage identification problem is treated in a hierarchical order, initialized by damage detection and moving to an increasingly more localized prediction of the damage location. Training datasets for the ML tools are generated from numerical finite element simulations. Measurement uncertainty is propagated in the theoretical strains by information inferred from experimental data. Two different sensor architectures were assessed. An experimental programme is performed for testing the accuracy of the proposed damage identification strategy, yielding promising results and providing valuable insights.

Defining hierarchical protein interaction networks from spectral analysis of bacterial proteomes

Cellular phenotypes emerge from a hierarchy of molecular interactions: proteins interact to form complexes, pathways, and phenotypes. We show that hierarchical networks of protein interactions can be extracted from the statistical pattern of proteome variation as measured across thousands of bacteria and that these hierarchies reflect the emergence of complex bacterial phenotypes. We describe the mathematics underlying our statistical approach and validate our results through gene-set enrichment analysis and comparison to existing experimentally-derived hierarchical databases. We demonstrate the biological utility of our unbiased hierarchical models by creating a model of motility in Pseudomonas aeruginosa and using it to discover a previously unappreciated genetic effector of twitch-based motility. Overall, our approach, SCALES (Spectral Correlation Analysis of Layered Evolutionary Signals), predicts hierarchies of protein interaction networks describing emergent biological function using only the statistical pattern of bacterial proteome variation.

Real-Time FPGA Accelerated Stereo Matching for Temporal Statistical Pattern Projector Systems

The presented paper describes a hardware-accelerated field programmable gate array (FPGA)–based solution capable of real-time stereo matching for temporal statistical pattern projector systems. Modern 3D measurement systems have seen an increased use of temporal statistical pattern projectors as their active illumination source. The use of temporal statistical patterns in stereo vision systems includes the advantage of not requiring information about pattern characteristics, enabling a simplified projector design. Stereo-matching algorithms used in such systems rely on the locally unique temporal changes in brightness to establish a pixel correspondence between the stereo image pair. Finding the temporal correspondence between individual pixels in temporal image pairs is computationally expensive, requiring GPU-based solutions to achieve real-time calculation. By leveraging a high-level synthesis approach, matching cost simplification, and FPGA-specific design optimizations, an energy-efficient, high throughput stereo-matching solution was developed. The design is capable of calculating disparity images on a 1024 × 1024(@291 FPS) input image pair stream at 8.1 W on an embedded FPGA platform (ZC706). Several different design configurations were tested, evaluating device utilization, throughput, power consumption, and performance-per-watt. The average performance-per-watt of the FPGA solution was two times higher than in a GPU-based solution.

On sensor optimisation for structural health monitoring robust to environmental variations

Structural health monitoring (SHM) is often approached from a statistical pattern recognition or machine learning perspective with the aim of inferring the health state of a structure using data derived from a network of sensors placed upon it. In this paper, two SHM sensor placement optimisation (SPO) strategies that offer robustness to environmental effects are developed and evaluated. The two strategies both involve constructing an objective function (OF) based upon an established damage classification technique and an optimisation of sensor locations using a genetic algorithm (GA). The key difference between the two strategies explored here is in whether any sources of benign variation are deemed to be observable or not. The relative performances of both strategies are demonstrated using experimental data gathered from a glider wing tested in an environmental chamber, with the structure tested in different health states across a series of controlled temperatures.