Особенности использования ключевых терминов в интеллектуальном реферате и научной статье в процессе сжатия текста (на материале английских текстов предметной области «Судостроение»)

The subject of the article is the processes of the automated analysis of server logs of software systems using Natural Language Processing methods. The goal is to develop an approach to improve the efficiency of log analysis by applying NLP algorithms and text compression methods. The tasks to be solved are: to study the features of logs as a source of technical information; to analyze modern methods of text data processing, including statistical, vector-based, and neural network approaches; to justify the feasibility of using NLP algorithms for automating log analysis; to substantiate the use of text compression methods to reduce data volume; and to develop a concept and architecture of an automated log analysis system. The methods used include: Natural Language Processing techniques such as TF-IDF, Word2Vec, FastText, and transformer-based models; text preprocessing methods; log compression and log template extraction approaches; and information retrieval methods applied to text corpora. The following results were obtained. A concept of an automated server log analysis system based on NLP methods and text compression algorithms was developed. A generalized system architecture was proposed, including modules for log collection, storage, filtering, preprocessing, text compression, NLP analysis, incident representation, and solution search. An algorithm for system operation was developed, providing step-by-step log processing while taking into account the textual nature and large volume of data. It was established that the use of NLP methods improves the accuracy of error detection and incident classification, while text compression reduces the computational load and increases system performance. Conclusions. The proposed approach improves the efficiency of software diagnostics, reduces the time required for error detection and resolution, and decreases the workload on developers. The scientific novelty of the obtained results lies in the following: an approach to automated log analysis combining NLP methods and text compression techniques was developed; a generalized architecture of a log analysis system that considers the specifics of unstructured textual data was proposed; existing log processing methods were further developed through the integration of modern NLP models with data volume optimization stages, which improves analysis efficiency in conditions of large-scale information flows

A novel algorithm for text compression is developed which consists of two parts. In the first part the text sample is encoded by the Ziv-Lempel asymptotic structured codebook. In the second part decoding is carried out by a novel rule based (RB) algorithm which improves the compression ratio for a given text sample by up to 50% when compared to the full text search as required by the Ziv-Lempel decoding algorithm.

We consider grammar based text compression with longest-first substitution, where non-overlapping occurrences of a longest repeating substring of the input text are replaced by a new non-terminal symbol. We present a new text compression algorithm by simplifying the algorithm presented in S. Inenaga et al., (2003). We give a new formulation of the correctness proof introducing the sparse lazy suffix tree data structure. We also present another type of longest-first substitution strategy that allows better compression. We show results of preliminary experiments comparing grammar sizes of the two versions of the longest-first strategy and the most frequent strategy

Text compression algorithms are normally defined in terms of a source alphabet Sigma of 8-bit ASCII codes. The authors consider choosing Sigma to be an alphabet whose symbols are the words of English or, in general, alternate maximal strings of alphanumeric characters and nonalphanumeric characters. The compression algorithm would be able to take advantage of longer-range correlations between words and thus achieve better compression. The large size of Sigma leads to some implementation problems, but these are overcome to construct word-based LZW, word-based adaptive Huffman, and word-based context modelling compression algorithms.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Trends Form Follows Function: New Ways to Inform and Inspire

Framing flexibility: Theorising and data mining to develop a useful definition of flexibility and related concepts

Reducing coding redundancy in LZW

Since its existence, the industry has experienced rapid developments. In this process, which began with the use of steam power, firms have now become witnesses to the effects of the fourth industry revolution with rapid developments in technology. The common use of technologies which are digital, the continuation of the developments in technology, has changed the business models, ways of doing business and Decision-making in many fields from the manufacturing industry to the service sector. energy industry is one of these fields. In this study, it is aimed to investigate the influences of transformation which is digital and processes starting with the use of digital technologies in the energy sector. For this purpose, a detailed literature survey based on scientific articles, annual activity and research reports of companies, white papers, has been performed. It has been researched in which areas the digital transformation shows its effect and then the research area in the energy industry has been narrowed in the same perspective. Herein, no scientific articles or reviews have been found in the literature. This reveals that there is a vacancy in the literature.

Introduction:As detailed in the 2018 ACGME Common Program Requirements statement for fellowship institutions, “The physician is a humanistic scientist who cares for patients. This requires the ability to think critically, evaluate the literature, appropriately assimilate new knowledge, and practice lifelong learning.” Endocrinology fellowship programs are tasked with the expectation of creating an environment that fosters scholarly pursuit. It is under the discretion of each program to consider its institutional resources and community needs in order to meet this ACGME requirement.1With the goal of enhancing trainee scholarly activity, our fellowship program created a Scholarly Activity Curriculum in 2017. The core curriculum pillars include delineating a yearly timeline of objectives and expectations, facilitating regular individual mentoring, permitting allotment of protected time, and advocating involvement in faculty scholarship and national conferences.Objective:To assess the impact of the 2017 Endocrinology Fellowship Scholarly Activity Curriculum with respect to its ability to increase trainee scholarship.Methods:The scholarly activities of the fellowship classes of 2017-2020 were extracted from archived Fellow Scholarly Activity Update presentations and exit-interview curricula vitae. The activities were categorized as conference presentations (oral/poster), basic scientific research, clinical scientific research, quality improvement, book chapters, review articles, case reports, and teaching activities. With the 2017 and 2018 classes representing the pre-curriculum study group and the 2019 and 2020 classes representing the post-curriculum study group, the number of activities per study group per scholarly category were tabulated and compared.Results:An increase in scholarly activity was noted in five of the delineated categories: conference presentations (80%), clinical scientific research (86%), review articles (100%), case reports (100%), and teaching activities (38%). The remaining three categories of basic scientific research, quality improvement, and book chapters showed no change.Conclusions:The implementation of the 2017 Endocrinology Fellowship Scholarly Activity Curriculum was associated with a rise in trainee scholarly activity. Four of eight categories showed an 80% or more increase. Interestingly, the fellows involved in basic scientific research both pre and post-curriculum implementation were limited to those in the Specialty Training and Advanced Research (STAR) Program. Finally, identifying the need to increase involvement in quality improvement research, our program has implemented a 2019 Quality Improvement Curriculum.1Common Program Requirements (Fellowship). ACGME. https://www.acgme.org/What-We-Do/Accreditation/Common-Program-Requirements. 2018. Accessed Nov 2019.

As a result of several questions and difficulties of some authors in understanding the difference between complete article and scientific note, as well as what is a review article, the objective of this editorial note is to clarify to editors, authors and readers of the Revista de Ciencias Agroveterinarias a the types of articles that are published in this journal. It is also included that this journal will standardize the types of articles, from 2018, as Research Article (full article), Research Note (scientific note) and Review Article (literature review). In addition, this journal publishes communications of the publishers as Nota Editorial. The three types of articles published by the journal, Research Article, Research Note and Review Article, are scientific articles derived from research conducted by the authors. Research articles and research notes are usually derived from original experimental research and, therefore, based on results obtained experimentally by the authors. Review articles are derived from non-experimental research, that is, not based on results obtained experimentally, but rather based on the knowledge (results and conclusions) generated so far on a given subject. Research article and research note are therefore similar according to their empirical basis. However, there are differences between these two types of articles that go beyond the extension of the text. Research notes are short, short texts with small results, but that generate unprecedented conclusion (s) as a result of a new fact discovered by the authors. In this way, its publication is justified due to the importance of the discovery, that is, of the scientific knowledge generated, even though there is not a large volume of results. Research articles are, in turn, longer texts, with greater volume of results, which also generate unprecedented conclusions as a result of new scientific discoveries. Therefore, it should be clear that research articles and research notes are equally important in the construction of scientific knowledge. Thus, an article with a small volume of results, in which the authors increase the information of the introduction and the discussion, in order to increase the number of pages, will not, in essence, be a complete article (Research Paper). Nor will a full article whose text is lean be characterized as a scientific note (Research Note), because its essence is not the same. So while overall articles are generally longer than scientific notes, it is not the number of pages that defines what is one and what is another. Review article, in turn, is not limited to the presentation (or meeting) of the scientific knowledge generated so far in a single article. Structurally, review articles are similar to full papers or scientific notes, presenting the justification, the objective, the methodology, the results (referring to the knowledge generated so far), the discussion (which is the author's critical view on the generated knowledge) and the conclusion (which is the unpublished scientific knowledge generated by the author, based on the scientific knowledge we had so far). Therefore, a review article should generate new scientific knowledge, not just gather information (knowledge) already present in the literature. Another type of scientific paper explored most recently is the meta-analysis. Meta-analysis is a synthesis of previous research on a (often polemical) subject, which emphasizes the production of quantitative conclusions, aiming at extracting additional information from pre-existing data through the union of the results of several works and the application of a or more statistical techniques (UFSM 2017). Meta-analysis is not derived from an original research, but from the analysis of previously published research, and therefore is included as Review Article. It is hoped, in conclusion, that the doubts regarding the articles published by the Revista de Ciencias Agroveterinarias have been remedied and that this brief note will help the writing of future works to be submitted and published in this journal.

Relevance of the problem of the development of technical means (GPR) and algorithms for processing ultra-wideband signals follows from the wide range of possibilities that these means of non-destructive testing and remote sensing provides, together with the potential of modern computing tools and software. Of particular interest in this regard are the results obtained by using various effects associated with a change in the polarization state of both primary (probing) pulses and signals reflected from complex multilayer media to detect defects in them. This is due to the possibility of not only quickly detecting heterogeneities, but also with the relatively low cost of such work. The purpose of the work is a review of various technical means (pulsed georadars) and signal processing methods for detecting various internal inhomogeneities in plane-layered media. These heterogeneities include, in addition to various internal communications elements (cables) and technical elements (drainage pipes), also dangerous externally invisible defects - subsurface cracks and delamination (interruption of contact between the layers). Materials and methods. The paper provides an overview of methods developed by the author, among others, which are designed to solve primarily the practical problems of detecting subsurface inhomogeneities and defects in plane-layered media. The physical basis for the creation of these methods was the result of many years of research by the author related to the analysis of the polarization state of complex (including pulsed) signals scattered by various objects. Results. The basis of the considered results is made up of both scientific articles and patents of Ukraine for inventions and utility models obtained by the author. Conclusions. The review of the results and various methods presented in the article is another confirmation of the wide possibilities offered by new means of remote sensing and non-destructive testing. These tools include not only the devices themselves (elements for obtaining primary data), but also information processing algorithms and software, combined into a single methodology for collecting, processing and subsequent storage of data on the current state of the examined technical and natural objects.

The purpose of this study was a historiographic analysis of scientific works on the history of zemstvos of the Middle Volga region, which contained assessments of the organization and activities of zemstvos of the provinces of the Middle Volga region, which, along with city councils, performed the functions of local governments in the second half of the XIX and early XX centuries. The focus is on regional studies. To reveal this topic, the authors set the following tasks: 1) to distinguish periods of historiography; 2) to find out the reasons for the insufficient attention of historians to the Zemstvo in Russian and Soviet historiography; 3) to show the most studied topics and problems raised in the research of Soviet and post-Soviet, as well as foreign historians in the field of Russian local government (including Samara); 4) to characterize the approaches of modern historiography of the Samara zemstvo; 5) to determine the objectives of future research. When studying the conceptual representations of scientists, the methods of historiographic analysis were used, including comparative-historical, chronological, and also the method of periodization. In the historiography of the problem, two periods are distinguished: Soviet and modern. Historiographic facts were used as a source base: the works of Soviet, Russian and foreign historians monographs, scientific articles, scientific reviews and critical reviews, which contain valuable information about the ideas of scientists on Zemstvos, depending on the socio-political situation in the country and the degree of development of the topic under study. The authors found that until the 60-ies of the XX century the history of zemstvos did not cause much interest, and assessments of their activities were in line with the Marxist-Leninist ideology; 19902000-ies the most active and fruitful period of research on the history of the zemstvo. In the 10 of the XXI century enthusiasm for this problem began to decline. After 2010, against the background of the process of integrating local self-government in the state vertical of power that is gaining momentum in Russia and reducing its political significance, the development of history of local self-government and the zemstvo direction in research have lost their popularity, although there are still unaffected aspects and the need to create generalized works has remained, so as a problem of the place of the self-government system in Russia the past, the present and the future has been and remains relevant for our country. The authors also attempted to identify a new vector of problems on the history of the Zemstvo movement in the Russian Empire.

On—line text—compression algorithms are considered, where compression is done by substituting substrings of the text according to some fixed dictionary (code book). Due to the long running time of optimal compression algorithms, several on—line heuristics have been introduced in the literature. In this paper we analyse two modified version of an old algorithm introduced by Shuegraf and Heaps [9]. We will investigate the worst case behaviour of this Longest Fragment First (LFF) algorithm for several types of special dictionaries.

The subject of study. A new algorithm for real-time data compression in a video surveillance system from an unmanned aerial vehicle is proposed. The algorithm makes it possible to obtain different degrees of video data compression using different codecs for specific video recording conditions (UAV altitude and flight speed, nature of the observed terrain, etc.), and also provides the ability to transmit video data to the flight control point via radio channel. A detailed analysis of the quality of the proposed algorithm for shooting in various video formats that meet international standards (HD and Full HD) was carried out, both in terms of visual perception and objective criteria. The purpose of the study was to conduct a comprehensive research on the problem of improving the quality of the video surveillance system from the UAV and to create a video compression algorithm that allows broadcasting video data to the control center in real time with high quality. Objectives. To develop and programmatically implement a video compression algorithm based on modern codecs for video surveillance sys­tems on board a UAV. To use modern video cameras and a microcomputer platform as hardware. To analyze the quality indicators of the algorithm in different conditions. Methods used. Evaluation of visual perception of video compression results, statistical analysis and processing of the parameters of the analyzed video sequence as a random spatio-temporal process. Results. A new video data compression algorithm for the UAV video surveillance system based on the Raspberry Pi 5 microcomputer using modern video compression codecs H.264 and H.265 was synthesized. The algorithm provides the required compression ratio and data transmission rate over the radio channel between the UAV and the flight control center. Detailed estimates of the quality of the algorithm are obtained. Conclusions. Scientific novelty of the results: A new universal video data compression algorithm for video surveillance systems on board UAVs with the ability to transmit video over a radio channel in real time has been proposed and implemented. The quality of the proposed algorithm is verified on real video surveillance results. The proposed algorithm is implemented in the Python software environment.

Data-driven research is key to producing evidence-based public policies, yet little is known about where data-driven research is lacking and how it can be expanded. We propose a method for tracking academic data use by country of subject in English-language social science and medicine articles, applying natural language processing to a large corpus of academic articles. The model’s predictions produce country estimates of the number of articles using data that are highly correlated with a human-coded approach, with a correlation of 0.99. Analyzing more than 140,000 academic articles, we find that high-income countries are the subject of ∼50% of all papers using data, despite only making up around 17% of the world’s population. Finally, we classify countries by whether they could most benefit from increasing their production or use of data, with the former applying to many poorer countries and the latter to many wealthier countries.