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Summary For cable bridges, the cable tension force plays a crucial role in their construction, assessment and long‐term structural health monitoring. Cable tension forces vary in real time with the change of the moving vehicle loads and environmental effects, and this continual variation in tension force may cause fatigue damage of a cable. Traditional vibration‐based cable tension force estimation methods can only obtain the time‐averaged cable tension force and not the instantaneous force. This paper proposes a new approach to identify the time‐varying cable tension forces of bridges based on an adaptive sparse time‐frequency analysis method. This is a recently developed method to estimate the instantaneous frequency by looking for the sparsest time‐frequency representation of the signal within the largest possible time‐frequency dictionary (i.e. set of expansion functions). In the proposed approach, first, the time‐varying modal frequencies are identified from acceleration measurements on the cable, then, the time‐varying cable tension is obtained from the relation between this force and the identified frequencies. By considering the integer ratios of the different modal frequencies to the fundamental frequency of the cable, the proposed algorithm is further improved to increase its robustness to measurement noise. A cable experiment is implemented to illustrate the validity of the proposed method. For comparison, the Hilbert–Huang transform is also employed to identify the time‐varying frequencies, which are then used to calculate the time‐varying cable‐tension force. The results show that the adaptive sparse time‐frequency analysis method produces more accurate estimates of the time‐varying cable tension forces than the Hilbert–Huang transform method. Copyright © 2016 John Wiley & Sons, Ltd.

The construction of corpus-based frequency dictionaries is shaped by two intertwined factors: the output of morphological analyzers and the way lexicographers organize headwords, two processes that are guided by how the construct of\"lemma\" is conceptualized. This article examines two contemporary Arabic frequency dictionaries (A Frequency Dictionary of Arabic: Core Vocabulary for Learners and A Frequency Dictionary of Contemporary Arabic Fiction: Core Vocabulary for Learners and Material Developers), with particular attention to challenges related to the organization of adverbs, singulative and collective nouns, and words that denote family and community members. The aim is to show that consideration for issues of derivation and inflection, semantic transparency, and lexicalization can help establish better criteria for organizing headwords from both pedagogical and corpus linguistics standpoints. The inconsistencies currently seen in Arabic frequency dictionaries point to multiple influencing factors, such as the role of Arabic morphological analyzers, the possible influence of Western lexicography and corpus linguistics, and the issue of how the lemma is conceptualized by computational tools and lexicographers alike.

Among the invertible orthogonal transforms employed to perform the analysis and synthesis of 2D signals (especially images), the ones defined by means of John von Neumann’s cardinal sinus are extremely interesting. Their definitions rely on transforms similar to those employed to process time-varying 1D signals. This article deals with the extension of John von Neumann’s transforms from 1D to 2D. The approach follows the manner in which the 2D Discrete Fourier Transform was obtained and has the great advantage of preserving the orthogonality property as well as the invertibility. As an important consequence, the numerical procedures to compute the direct and inverse John von Neumann’s 2D transforms can be designed to be efficient thanks to 1D corresponding algorithms. After describing the two numerical procedures, this article focuses on the analysis of their performance after running them on some real-life images. One black and white and one colored image were selected to prove the transforms’ effectiveness. The results show that the 2D John von Neumann’s Transforms are good competitors for other orthogonal transforms in terms of compression intrinsic capacity and image recovery.

The article describes theoretical issues, principles of constructing and functioning of the Automated System of Morphemic and Derivational Analysis (ASMDA). The ASMDA system performs the following functions: 1) information system; 2) automatic morphemic annotation of text; 3) automatic linguistic constructor for frequency dictionaries. Description of the use of ASMDA as an automatic morphemic analyser of Ukrainian texts’ lexicon is in the centre of attention; this article also describes structure as well as search and classification options of electronic morphemic dictionaries presented in linguistic research system of the Corpus of the Ukrainian language.

Monitoring physiological functions such as swallowing often generates large volumes of samples to be stored and processed, which can introduce computational constraints especially if remote monitoring is desired. In this article, we propose a compressive sensing (CS) algorithm to alleviate some of these issues while acquiring dual-axis swallowing accelerometry signals. The proposed CS approach uses a time-frequency dictionary where the members are modulated discrete prolate spheroidal sequences (MDPSS). These waveforms are obtained by modulation and variation of discrete prolate spheroidal sequences (DPSS) in order to reflect the time-varying nature of swallowing acclerometry signals. While the modulated bases permit one to represent the signal behavior accurately, the matching pursuit algorithm is adopted to iteratively decompose the signals into an expansion of the dictionary bases. To test the accuracy of the proposed scheme, we carried out several numerical experiments with synthetic test signals and dual-axis swallowing accelerometry signals. In both cases, the proposed CS approach based on the MDPSS yields more accurate representations than the CS approach based on DPSS. Specifically, we show that dual-axis swallowing accelerometry signals can be accurately reconstructed even when the sampling rate is reduced to half of the Nyquist rate. The results clearly indicate that the MDPSS are suitable bases for swallowing accelerometry signals.

John von Neumann (JvN) was one of the greatest scientists and minds of the 20th century. His research encompassed a large variety of topics (especially from mathematics), and the results he obtained essentially contributed to the progress of science and technology. Within this article, one function that JvN defined long time ago, namely the cardinal sinus (sinc), was employed to define transforms to be applied on 1D signals, either in continuous or discrete time. The main characteristics of JvN Transforms (JvNTs) are founded on a theory described at length in the article. Two properties are of particular interest: orthogonality and invertibility. Both are important in the context of data compression. After building the theoretical foundation of JvNTs, the corresponding numerical algorithms were designed, implemented and tested on artificial and real signals. The last part of the article is devoted to simulations with such algorithms by using 1D signals. An extensive analysis on JvNTs effectiveness is performed as well, based on simulation results. In conclusion, JvNTs prove to be useful tools in signal processing.

The article presents the algorithm of the frequency dictionary to an original ancient text, “Otpys” (“Response”) by Kliryk Ostrozkyi (the Cleric of Ostroh) of the late 16 century. Until now, no historical corpus of text of the Ukrainian language has been created; therefore the drafting of metagraphical texts with their subsequent processing in accordance with linguistic tasks can fill this gap. The peculiarity of creating a frequency dictionary based on one written monument is in using the model of frequency dictionaries and describing the specifics of processing the ancient text. These specifics is based on a deep understanding of the state of language in the end of the 16 century and consists in the unification of graphic and spelling variants, as well as in the formation of stems and lemmas. Work results are presented in the form of a Frequency Dictionary of Word Forms of “Otpys” by Kliryk Ostrozkyi according to the frequency decrease and a Frequency Dictionary of “Otpys” by Kliryk Ostrozkyi according to the frequency decrease.

The paper presents a novel approach to study a nucleotide sequence structure with respect to the chloroplast genome DNA sequence analysis. A specific frequencies distribution pattern of the consecutive triple nucleotide fragments was identified in the chloroplast genome DNA sequence, which demonstrated a non-degenerated pattern with seven clusters.

The paper presents a novel approach to infer a structuredness in a set of symbol sequences such as transcriptome nucleotide sequences. A distribution pattern of triplet frequencies in the Siberian larch (Larix sibirica Ledeb) transcriptome sequences was investigated in the presented study. It was found that the larch transcriptome demonstrates a number of unexpected symmetries in the statistical and combinatorial properties.

The spatial distribution of GC content of fragments of the genomes of chloroplasts, mitochondria and bacteria was considered. It was found that the GC content of fragments of most genomes were distributed not chaotically, but in an orderly manner. Two principal types of distribution were found, gradient and centrally symmetric. Chloroplast genomes had only a gradient distribution. Bacteria had a centrally symmetric distribution for GC-poor genomes, and a gradient distribution for GC-rich ones. Both types of distributions occurred in mitochondria; the type of distribution depended on the type of organism.