On approximations by trigonometric polynomials of classes of functions defined by moduli of smoothness

In this paper, we give a characterization of Nikol'ski\u{\i}-Besov type classes of functions, given by integral representations of moduli of smoothness, in terms of series over the moduli of smoothness. Also, necessary and sufficient conditions in terms of monotone or lacunary Fourier coefficients for a function to belong to a such a class are given. In order to prove our results, we make use of certain recent reverse Copson- and Leindler-type inequalities.Comment: 18 pages. arXiv admin note: substantial text overlap with arXiv:1208.612

Investigating the Effects of Word Substitution Errors on Sentence Embeddings

A key initial step in several natural language processing (NLP) tasks involves embedding phrases of text to vectors of real numbers that preserve semantic meaning. To that end, several methods have been recently proposed with impressive results on semantic similarity tasks. However, all of these approaches assume that perfect transcripts are available when generating the embeddings. While this is a reasonable assumption for analysis of written text, it is limiting for analysis of transcribed text. In this paper we investigate the effects of word substitution errors, such as those coming from automatic speech recognition errors (ASR), on several state-of-the-art sentence embedding methods. To do this, we propose a new simulator that allows the experimenter to induce ASR-plausible word substitution errors in a corpus at a desired word error rate. We use this simulator to evaluate the robustness of several sentence embedding methods. Our results show that pre-trained neural sentence encoders are both robust to ASR errors and perform well on textual similarity tasks after errors are introduced. Meanwhile, unweighted averages of word vectors perform well with perfect transcriptions, but their performance degrades rapidly on textual similarity tasks for text with word substitution errors.Comment: 4 Pages, 2 figures. Copyright IEEE 2019. Accepted and to appear in the Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing 2019 (IEEE-ICASSP-2019), May 12-17 in Brighton, U.K. Personal use of this material is permitted. However, permission to reprint/republish this material must be obtained from the IEE

The European performance indicators of broiler chickens as influenced by stocking density and sex

ArticleThe aim of this study was to investigate the influence of different stocking densities on the growth performance of Ross 308 broiler chickens up to six weeks of age. A to tal of 216 one - day broiler chicks were randomly assigned to three treatment groups based on the stocking density: Low (LSD) = 14 chickens m - 2 , Medium (MSD) = 18 chickens per m 2 and High (HSD) = 22 chickens m - 2 , with four replications. Higher body weight gain (TWG) was observed for the low (2,043.89 g) and medium (2 , 008.03 g) compared to the high (1,901.51 g) density. The study revealed that chickens of the LSD treatment consumed significantly ( P < 0.01) more fe ed compared to the HSD chickens. High stocking density (22 m - 2 ) tended to improve feed conversion ratio compared to medium (18 m - 2 ) and low (14 m - 2 ) stocking density, but the differences were not significant ( P > 0.05). From the results of this study it can be concluded that broiler chicks can be stocked up to 22 chickens m 2 , as far as required standards are assured