scholarly journals Diachronic Changes in the Frequency of Color Designation in Russian Poetic Texts

2021 ◽  
Vol 19 (4) ◽  
pp. 5-35
Author(s):  
A. Ts. Masevich ◽  
V. P. Zakharov
Keyword(s):  
Corpus Linguistics ◽  
18Th Century ◽  
Semantic Annotation ◽  
Quantitative Characteristic ◽  
General Description ◽  
Black And White ◽  
Part Of Speech ◽  
Poetic Texts ◽  
Frequency Behavior

We propose a statistical-diachronic approach to the description of color designations in poetic texts in Russian. Methods of corpus linguistics and the semantic annotation of the Russian National Corpus (RNC) applied in the research have revealed certain patterns of change in the frequency ` in poetic texts from 1750 to 1999. A quantitative characteristic of the poetic corpus of the RNC is presented by decades of the period under study. We also provide a general description of its poetry corpus (number of texts, number of authors, searching techniques, the semantic annotation, etc.). Also presented is the authors' classification of adjectives with the color tag of the semantic annotation.The study has revealed the RNC inconsistency in the assignment of color tags during the semantic annotation. In the authors’ opinion, this defect could affect the results of the study; however, the spotted tendencies in frequency behavior of color adjectives seem to be reliable.The research method is based on the comparison of statistical indicators for each decade in the specified range. Accordingly, the charts are plotted with reference to the average values for the range, unlike the RNC Charts tool, where a chart is based on the points for each year with a smoothing coefficient. Also, the indicators in the poetic corpus are compared with the corresponding data in the prose corpus. It has been reliably established that in the texts of the poetry corpus the frequency of color designations is higher than in the texts from basic, newspaper and oral corpora regardless of the part of speech the words belong to. The highest frequency (IPM) values of all adjectives that have the color tag of the RNC semantic annotation are observed in the last decades of the 19th - first decades of the 20th centuries. The frequency behavior of adjectives belonging to different classes differs significantly in different periods. In the texts of the 18th century, the analogous adjectives (or the adjectives of secondary nomination, such as златой (golden), янтарный (amber), etc.) prevail. In the texts of the 19th century adjectives – quasi-colors, (such as светлый (light), тёмный (dark), бледный (pale), etc.) are most frequent whereas in the texts of the 20th century the color adjectives per se have the highest frequency. While ranking the data selected from all the periods in the descending order, the first 28 ranks were occupied by the adjectives denoting achromatic colors – black and white. The article also defines prospects for our further research of color designations in Russian: specifying classification of color adjectives, looking at statistical aspects of their polysemy, and comparison of their use frequency by individual authors.

Problems of Legal Regulation Tourism Safety Problems and Ways to Solve Them

2021 ◽  
Vol 12 (2) ◽  
pp. 515
Author(s):  
Valerii TATSIIENKO ◽  
Ivan MIROSHNYKOV ◽  
Volodymyr KROITOR ◽  
Alevtina BIRIYKOVA ◽  
Elvira ORZHYNSKA ◽  
...  
Keyword(s):  
Legal Regulation ◽  
General Description ◽  
History Of

The article provides a general description of the safety of tourism, namely: the history of the issue of ensuring safety in tourism is analyzed, the concept, types and tasks of tourism safety are revealed, and the classification of risks (threats) and sources of danger in the field of tourism is considered; defined the concept, structure and content of the administrative and legal institute of tourism safety, and also disclosed the legal regulation in the field of tourism safety; disclosed the concept and content of administrative and legal tourism safety regime, classify it into types (sub-regimes); describes the administrative and legal measures to ensure the safety of tourism; highlighted the main security problems in the field of tourism and formulate ways to solve them. The purpose of the thesis is a comprehensive and comprehensive research theoretical and practical problems of administrative and legal ensuring the safety of tourism.

scholarly journals Recovery of a vandalized canvas painting our Lady of the Rosary from Vrlika (Croatia)

2020 ◽  
Vol 18 (1) ◽  
pp. 247-257
Author(s):  
Sandra Sustic ◽  
Ivan Rezic ◽  
Mario Cvetkovic
Keyword(s):  
Visual Analysis ◽  
18Th Century ◽  
Paint Layer ◽  
General Factor ◽  
Oil Painting ◽  
War Of Independence ◽  
Black And White ◽  
Parish Community ◽  
Visual Materials ◽  
Painting On Canvas

This study is related to the major recovery project of an 18th century oil painting on canvas depicting Our Lady of the Rosary, the patron saint of the parish community of Vrlika and its surroundings. During the Croatian War of Independence in 1992 it was taken off the main altar and vandalized by the paramilitary units. This resulted in termination of a century long tradition of annual feasts in Vrlika in which the painting was publicly displayed and carried by the townsmen. Based on the available visual materials: a high resolution old black and white photograph and the low resolution coloured one, respectfully, using the computer colorization algorithm, and also relying on detailed visual analysis of the original paint layer, a major reconstruction was carried out in 2017. This research has demonstrated that the recovery of the artworks with dramatic losses is an extremely complex social phenomenon difficult to characterize by any general factor or based on any general approach.

scholarly journals [Woman]’s World Portrayed in Literary Works of Jane Austen

2018 ◽  
Vol 12 (1) ◽  
pp. 77
Author(s):  
Gusti Ayu Praminatih ◽  
Homsatun Nafiah
Keyword(s):  
Qualitative Method ◽  
Jane Austen ◽  
18Th Century ◽  
Domestic Sphere ◽  
Literary Works ◽  
Part Of Speech ◽  
Abstract Nouns

The researchers conducted research on Jane Austen literary works since she was a prominent female novelist with mostly discussed novels. The aim of this research was investigating how Jane Austen portrayed [woman] in the18th century through literary works. Six major novels were used as data. Hence qualitative method was employed. The novels were converted using AntConc. Then, the researchers identified the 50 highest collocations of [woman] based on three main categories in part of speech namely adjective, noun, and verb. The results reveal that Jane Austen portrays [woman] in the 18th century with positive and negative aspects; internal and external qualities that reflected through adjectives. Jane Austen often uses concrete and abstract nouns related to domestic property collocated with the word [woman]. Furthermore, the verbs that collocate with [woman] in Jane Austen’s literary works are productive verbs. The researchers find that the adjectives, nouns, and verbs that attach to [woman] in Jane Austen novels are related to the domestic sphere and their quality of being strong, logical, and intellectual.

scholarly journals A Probability based Classification of Named Entities for Malayalam Language combining Word, Part of Speech and Lexicalized features

2019 ◽  
Vol 8 (2) ◽  
pp. 839-842
Keyword(s):  
Named Entity Recognition ◽  
Entity Recognition ◽  
Supervised Machine Learning ◽  
Named Entities ◽  
Named Entity ◽  
Domain Specific ◽  
Part Of Speech ◽  
Classification Probability ◽  
Malayalam Language

Named Entity Recognition is the process wherein named entities which are designators of a sentence are identified. Designators of a sentence are domain specific. The proposed system identifies named entities in Malayalam language belonging to tourism domain which generally includes names of persons, places, organizations, dates etc. The system uses word, part of speech and lexicalized features to find the probability of a word belonging to a named entity category and to do the appropriate classification. Probability is calculated based on supervised machine learning using word and part of speech features present in a tagged training corpus and using certain rules applied based on lexicalized features.

Analysing the features of negative sentiment tweets

2018 ◽  
Vol 36 (5) ◽  
pp. 782-799 ◽  
Author(s):  
Ling Zhang ◽  
Wei Dong ◽  
Xiangming Mu
Keyword(s):  
Research Area ◽  
Small Sample ◽  
Negative Word ◽  
Social Media Data ◽  
Content Type ◽  
Word Use ◽  
Part Of Speech ◽  
Negative Sentiment ◽  
Media Data

Purpose This paper aims to address the challenge of analysing the features of negative sentiment tweets. The method adopted in this paper elucidates the classification of social network documents and paves the way for sentiment analysis of tweets in further research. Design/methodology/approach This study classifies negative tweets and analyses their features. Findings Through negative tweet content analysis, tweets are divided into ten topics. Many related words and negative words were found. Some indicators of negative word use could reflect the degree to which users release negative emotions: part of speech, the density and frequency of negative words and negative word distribution. Furthermore, the distribution of negative words obeys Zipf’s law. Research limitations/implications This study manually analysed only a small sample of negative tweets. Practical implications The research explored how many categories of negative sentiment tweets there are on Twitter. Related words are helpful to construct an ontology of tweets, which helps people with information retrieval in a fixed research area. The analysis of extracted negative words determined the features of negative tweets, which is useful to detect the polarity of tweets by machine learning method. Originality/value The research provides an initial exploration of a negative document classification method and classifies the negative tweets into ten topics. By analysing the features of negative tweets, related words, negative words, the density of negative words, etc. are presented. This work is the first step to extend Plutchik’s emotion wheel theory into social media data analysis by constructing filed specific thesauri, referred to as local sentimental thesauri.

Abstract P118: Machine Learning Algorithm For Improving Classification Of Myocardial Infarction Across A Diverse Population Using US Veteran Electronic Health Record Data

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Kelly Cho ◽  
Nicholas Link ◽  
Petra Schubert ◽  
Zeling He ◽  
Jacqueline P Honerlaw ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Myocardial Infarction ◽  
Density Lipoprotein ◽  
Health Record ◽  
Female Veterans ◽  
Black And White ◽  
Code Algorithm ◽  
Billing Code

Introduction: The majority of population-based studies of myocardial infarction (MI) rely on billing codes for classification. Classification algorithms employing machine learning (ML) increasingly used for phenotyping using electronic health record (EHR) data. Hypothesis: ML algorithms integrating billing and information from narrative notes extracted using natural language processing (NLP) can improve classification of MI compared to billing code algorithms. Improved classification will improve power to compare risk factors across population subgroups. Methods: Retrospective cohort study of nationwide Veterans Affairs (VA) EHR data. MI classified using 2 approaches: (1) published billing code algorithm, (2) published phenotyping pipeline incorporating NLP and ML. Results compared against gold standard chart review of MI outcomes in 308 Veterans. We also tested known association between high density lipoprotein cholesterol (HDL-C) and MI outcomes classified using the 2 approaches among Black and White Veterans, stratified by sex and race; prior study showed HDL-C less protective for Black compared to White individuals. Results: We studied 17,176,658 million Veterans, mean age 69 years, 94% male, 12% self-report Black, 71% White. The billing code algorithm classified MI at positive predictive value (PPV) 0.64 compared to the published ML approach, PPV 0.90; the latter classified a modestly higher percentage of non-White Veterans. Using ML algorithm for MI, we replicated a reduced protective effect of HDL-C in Black vs White male and female Veterans (Table); with the billing code algorithm no association was observed between low density lipoprotein cholesterol (LDL-C) or HDL-C with MI among Black female Veterans. Conclusions: Using nationwide VA data, application of an ML approach improved classification of MI particularly among non-White Veterans, resulting in improved power to study differences in association for MI risk factors among Black and White Veterans.

Application of the LDA Model to Semantic Annotation of Web-based English Educational Resources

2021 ◽  
Author(s):  
Wei Du ◽  
Haiyan Zhu ◽  
Teeraporn Saeheaw
Keyword(s):  
Topic Modeling ◽  
Basic Education ◽  
Semantic Annotation ◽  
Experimental Results ◽  
Educational Resources ◽  
Metadata Standard ◽  
Web Based ◽  
Teaching Content ◽  
Macroscopic Classification

Based on the LDA model, this paper builds a three-layer semantic model of Web English educational resources “document-topic-keyword”, models the semantic topics of resource documents, and obtains the semantic topics and keywords of document resources as the semantic labels of resources. The experimental results show that document LDA topic modeling is beneficial to the macroscopic classification of Web English educational resources. The experimental results show that LDA topic modeling of documents is useful for macroscopic cataloging of Web English educational resources, highlighting teaching priorities, difficulties, and interrelationships, while LDA modeling of teaching topics with the same teaching content expands the metadata generation method of resource description based on the basic education metadata standard and provides more information about the inherent characteristics of resources. The semantic information can be used to mine the semantic thematic features and detailed differences inherent in the resources, and the final performance analysis verifies the parallel computing advantages of the LDA model in a big data environment.

A New Handwritten Dictionary of the Komi-Zyryan Language in the History of Komi Lexicography

2021 ◽  
pp. 87-104
Author(s):  
Galina V. Fedyuneva ◽  
Keyword(s):  
18Th Century ◽  
Native Speakers ◽  
Native Speaker ◽  
17Th Century ◽  
Historical Interpretation ◽  
Old Russian ◽  
History Of ◽  
Lexical Composition ◽  
Russian Dictionary

The article presents an analysis of the lexical composition of the newly discovered Zyryan-Russian dictionary of the 17th century and clarifies its place in the history of Komi lexicography. The article solves the problems of classification of lexicographic monuments and systematization of approaches to their description, and reveals gaps in research that has not been conducted since the mid-20th century. The currently known lexicographic monuments of the Komi language are limited to the dictionary materials of D.G. Messerschmidt, F.I. Stralenberg, G.F. Miller, P.S. Pallas and I.I. Lepekhin; the materials were collected during their expeditions in the 1720s–1770s. Unlike the church monuments of the Old Komi language of the 14th–17th and 18th centuries, the materials have not yet received a thorough archaeographic description, textual analysis and cultural and historical interpretation. The new Zyryan-Russian dictionary, discovered as part of the manuscript collection of the monk Prokhor Kolomnyatin and accurately dated (1668), is the earliest monument in the history of Komi lexicography today. The dictionary is interesting because it belongs to the period almost undocumented by written evidence and differs from all existing monuments in its dialect basis. The article describes the structure of the dictionary, thoroughly analyzes the lexical composition and presents most of its content, and reveals parallels with the dictionary materials of other monuments. The Russian-Komi dictionary-phrasebook that I.I. Lepekhin found and published in his Diary Notes is considered in more detail. Later V.I. Lytkin reprinted and deciphered the phrasebook, as well as made commentaries on it in his Old Permic Language (1952); thus, it became an auxiliary material for the reconstruction of the Old Komi language of the 14th–17th centuries. The dictionary dates back to the 18th century, although it has not been subjected to serious cultural-historical and chronological attribution. The newly discovered monument, unlike Lepekhin’s dictionary created by the type of translated old Russian dictionaries-phrasebooks based on the Russian questionnaire, reflects the live Komi-Zyryan language of the second half of the 17th century. It does not contain typical phrases, phrases from dialogues and connected texts that are typical of translated phrasebooks. There is only a certain tendency towards a thematic presentation of the material, although not always consistent. Like the dictionary materials contained in the draft papers of Russian and foreign travellers of the 18th century, the vocabulary of the new dictionary was written by the author of the collection directly from the words of a native speaker (or native speakers) of the Komi language in order to fix it and, apparently, was not intended for communicative use. Unlike the existing dictionary materials, which often contain short lists of Komi numerals, the new dictionary contains a consistent detailed money vocabulary list, from “denga” to “thousand rubles”. Numerical values are given in the Cyrillic numeral system using letters, which is undoubtedly of interest for ethnohistorical research and Russian paleography.

From Dalton to the Discovery of the Periodic System

2013 ◽  
Author(s):  
Eric Scerri
Keyword(s):  
Periodic System ◽  
Quantitative Data ◽  
Quantitative Characteristic ◽  
Good Deal ◽  
Ancient Greek ◽  
System P ◽  
Quantitative Property ◽  
To Come ◽  
First Time

Our story begins, somewhat arbitrarily, in the English city of Manchester around the turn of the nineteenth century. There, a child prodigy by the name of John Dalton, at the tender age of fifteen is teaching in a school with his older brother. Within a few years, John Dalton’s interests have developed to encompass meteorology, physics, and chemistry. Among the questions that puzzle him is why the various component gases in the air such as oxygen, nitrogen, and carbon dioxide do not separate from each other. Why does the mixture of gases in the air remain as a homogeneous mixture? As a result of pursuing this question, Dalton develops what is to become modern atomic theory. The ultimate constituents of all substances, he supposes, are hard microscopic spheres or atoms that were first discussed by the ancient Greek philosophers and taken up again by modern scientists like Newton, Gassendi, and Boscovich. But Dalton goes a good deal further than all of these thinkers in establishing one all-important quantitative characteristic for each kind of atom, namely its weight. This he does by considering quantitative data on chemical experiments. For example, he finds that the ratio for the weight in which hydrogen and oxygen combine together is one to eight. Dalton assumes that water consists of one atom of each of these two elements. He takes a hydrogen atom to have a weight of 1 unit and therefore reasons that oxygen must have a weight of 8 units. Similarly, he deduces the weights for a number of other atoms and even molecules as we now call them. For the first time the elements acquire a quantitative property, by means of which they may be compared. This feature will eventually lead to an accurate classification of all the elements in the form of the periodic system, but this is yet to come. Before that can happen the notion of atoms provokes tremendous debates and disagreements among the experts of Dalton’s day.

scholarly journals Negative constructions with “Hem” (no) influencing the choice of the genitive form of nouns

2019 ◽  
Vol 69 ◽  
pp. 00086
Author(s):  
Lydia Ogorodnikova ◽  
Yulia Ryndina
Keyword(s):  
18Th Century ◽  
Russian Language ◽  
Double Negation ◽  
Structural Types ◽  
Literary Sources ◽  
Russian Literary ◽  
Long Time ◽  
The Russian Language ◽  
Genitive Case

The article presents a further study of the genitive case variant inflection distribution in inanimate masculine nouns, found in fiction and journalistic texts of the second half of the 18th century. The focus is on the double negation in impersonal-predicative constructions with the word “no”. The relevance of the study is due to the persistent ambiguity of the choice of the genitive case form of words. The novelty is due to the literary sources created during the norm-establishing phase of the Russian literary language development. The article describes forms of the genitive case that have existed in the Russian language for a long time. The authors interpret the mechanism for choosing the genitive case by the authors of fiction and journalistic texts. The authors argue that a negative construct as a syntactic factor has little effect on the choice of the genitive case. The article discusses results of the comparative analysis of noun forms with A- and y-endings. In all types of negative constructions, the A-ending predominates, whereas the y-ending is observed in adverbial constructions and emphatic negations. A classification of structural types of negative sentences with genitive forms was developed.

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