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Nowadays there are a lot of modern technologies in electronic lexicography: speech synthesis technology, cross-referencing between dictionary modules, spell-checking functions, etc. The increasing availability of online information has necessitated intensive research in the area of automatic text summarization within the Natural Language Processing community. Belarusian scientists are also interested in this sphere and new lexicographical approaches for creating a linguistic database are shown in the paper. The authors present English-Belarusian-Russian electronic dictionary TechLex. This is the project of the 2nd English Department and the Department of Software for Information Systems and Technologies of the Belarusian National Technical University. The linguistic database of the dictionary is compiled not by the traditional method of processing a large number of paper dictionaries and combining the received translations, but by sequential processing of scientific and technical English-language periodicals. While the designing the dictionary the authors have taken into account the analysis of modern electronic multilingual translation dictionaries and created a client-server application in the Java programming language. The client part of the system contains a mobile application for the Android operating system, which has been tested on tablets and smartphones with different screen diagonals. The interface of the TechLex dictionary is designed taking into account the possibility of adding new subject areas and filling them with appropriate lexical material. The main advantage of our dictionary is that it is the first technical multilingual electronic dictionary having a Belarusian version.

The paper deals with a problem of the obfuscated JavaScript code detection and classification based on Abstract Syntax Trees (AST) coloring. Colors of the AST vertexes and edges are assigned with regard to the types of the AST vertexes specified by the program lexical and syntax structure and the programming language standard. Research involved a few stages. First of the all, a non-obfuscated JavaScript programs dataset was collected by the public repositories evaluation. Secondly, obfuscated samples were created using eight open-source obfuscators. Classifier models were built using an algorithm of gradient boosting on the decision trees (GBDT). We built two types of the classifiers. The first one is the model that classifies the program according to the type of the obfuscator used, i.e. based on what obfuscator created the sample. The second one tries to detect samples obfuscated by the obfuscator whose samples are not observed during training. The quality of the obtained models is on par with the known published results. The feature engineering method proposed in the paper does not require a preliminary analysis of the obfuscators and obfuscating transformations. In the final part of the paper we analyze a quality of models estimated, discussing the certain statistical properties of the obfuscated and non-obfuscated samples obtained and corresponding colored ASTs. Analysis of generated samples of obfuscated programs has shown that the method proposed in the paper has some limitations. In particular, it is difficult to recognize minifiers or other obfuscating programs, which change the lexical structure to a greater extent and the syntax to a lesser extent. To improve the quality of detection of this kind of obscuring transformations, one can built combined classifiers using both the method based on the AST coloring and the additional information about lexemes and punctuation, for example, entropy of identifiers and strings, proportion of characters in upper and lower case, usage frequency of certain characters etc.

This paper suggests an approach to the semantic image analysis for application in computer vision systems. The aim of the work is to develop a method for automatically construction of a semantic model, that formalizes the spatial relationships between objects in the image and research thereof. A distinctive feature of this model is the detection of salient objects, due to which the construction algorithm analyzes significantly less relations between objects, which can greatly reduce the image processing time and the amount of resources spent for processing. Attention is paid to the selection of a neural network algorithm for object detection in an image, as a preliminary stage of model construction. Experiments were conducted on test datasets provided by Visual Genome database, developed by researchers from Stanford University to evaluate object detection algorithms, image captioning models, and other relevant image analysis tasks. When assessing the performance of the model, the accuracy of spatial relations recognition was evaluated. Further, the experiments on resulting model interpretation were conducted, namely image annotation, i.e. generating a textual description of the image content. The experimental results were compared with similar results obtained by means of the algorithm based on neural networks algorithm on the same dataset by other researchers, as well as by the author of this paper earlier. Up to 60 % improvement in image captioning quality (according to the METEOR metric) compared with neural network methods has been shown. In addition, the use of this model allows partial cleansing and normalization of data for training neural network architectures, which are widely used in image analysis among others. The prospects of using this technique in situational monitoring are considered. The disadvantages of this approach are some simplifications in the construction of the model, which will be taken into account in the further development of the model.

The paper analyses the known available method to search for the author of the text in the natural language base of knowledge proposed by O. Khrulev in which the minimum distance between the frequency dictionaries of the presumed authors and the text under analysis is accepted as a criterion for the successful identification of the author. The patterns and drawbacks of the method are revealed.The paper suggested that since the distance value is based on the average values of this lexeme-usage in all papers of the author on the basis of which frequency dictionaries are created, such leaps will show up when the specific value of the lexeme-usage frequency stands in stark difference to the average one.To test this hypothesis, the paper determines a variation coefficient of each lexeme-usage frequency in the texts under analysis.The analysis of frequency dictionaries of Russian canonical writers conducted in the paper has shown that on average about 90% of the authors' frequency dictionaries contain lexemes whose frequencies of usage are inhomogeneous.The author of the paper suggested that the coefficient of variation shows increase in author's word-hoard, i.e. the larger the vocabulary size, the richer the speech, and, therefore, the less frequently the author uses the same lexemes.In the paper there is a hypothesis that it is wrong to reduce the analysed size of the authors' frequency dictionaries only by critical boundaries: it is necessary to analyse lexemes with a variation coefficient over 33%, which illustrate rich word-hoard.The paper also proposes to define only one specific critical boundary of 10 thousand lexemes, since the indefinite boundary of 5 - 10 thousand lexemes offered by O. Khrulev makes it difficult to identify the author of unknown text. In this case, the lexemes with a variation coefficient over 33% of the total vocabulary size of the studied authors beyond the critical boundary are subjected to analysis.To test this hypothesis, a numerical experiment was carried out. The main point of the experiment was to identify the authors of unknown texts based on the authors' frequency dictionaries. At the same time, there were no unknown texts in the data compilation of the frequency dictionaries. The identification was based on the calculation of distance from the unknown text to the authors' frequency dictionaries, i.e. according to O. Khrulev’ s technique. In calculation different critical boundaries were specified.A numerical experiment has shown that the method proposed in the paper increases the successful identification percent for the larger size texts (more than 5,000 word forms) by 12.5%, and for texts of small size (less than 5,000 word forms) by 15.2%.

The paper explores the key problems of establishing the type of negative information and differentiating between facts and opinions. This is one of the most challenging problems of forensic linguistics that requires a robust methodological framework to be tackled successfully. When faced with this problem, the expert has to deal with the ambiguity of terminology and wording of questions, as well as the complexity of the object of study – the semantics of statements encountered in acts of speech. The paper analyzes the content of key terms traditionally used to address this forensic problem, and offers a possible solution. The so-called “factual square” is a method based on analyzing a statement against four semantic parameters: presence of statement of past action; verifiability of this statement on the basis of specificity of description of the action and its potential observability; lack of alternative, i.e. indication of a different possibility; the purpose of conveying negative information. The paper also analyzes the basic types of factual information and offers specific examples of semantic analysis of statements using the proposed approach.

В статье рассматривается апробация интегративной методики атрибуционного анализа текста на русском языке., This paper focuses on the approbation of an integrative method of attribution text analysis in Russian, based on a combination of the results of an interpretive study of the material and objectification of these results through mathematical statistics., Политическая лингвистика, Issue № 3 (81), Pages 215-224

В статье рассматриваются вопросы, посвященные графической форме существования языка, выраженной в шрифтовом начертании. Шрифтовой знак — буква — интересен как объект дизайна и как объект визуального искусства. Изучение его значения в визуальной системе коммуникаций определяет актуальность темы. Также в работе анализируется значимость изучения связи зрительного образа и его восприятия., The paper discusses the issues related to the graphical form of the language, expressed in the font style. Font sign, a letter, is interesting as an object of design and as an object of visual art. The study of its signifi cance in the visual communication system determines the relevance of the topic. Along with this, the work reinterprets its methodological signifi cance. Materials are proposed for theoretical and practical exercises., Университетский научный журнал, Выпуск 57 2020

Introduction. The study is concerned with revealing specific aspects of use of implicit knowledge when combined sequence is learned. The paper focuses on the problem of unconscious perception of multiple information. Unlike most of other researches in implicit learning, the present study probes into implicit knowledge usage under condition of conscious manipulation of one of several parameters in combined sequence. The aim of the study is to reveal aspects of implicit knowledge use in combined sequences learning. Materials and Methods. “Sequences learning” experimental technique was implemented to find out attributes of implicit knowledge gaining and usage in sensomotor tasks. 9 geometrical figures of different forms and colours were exposed 15 times sequentially in the certain order during the training phase of the study. Participants were asked to press certain key after a figure of relevant form appeared on the screen as quick as they can. During the test phase that followed, participants were asked to press a certain key after a figure of relevant colour appeared on the screen. Conditions varied depending on whether one or another pattern (by form or by color) was implemented in the sequence of stimulus. Time of sensorimotor reaction in serial reaction task was used as empirical marker of learning efficacy. The procedure was carried out on a typical serial laptop with screen resolution 1366x768 pixels running a program specially written for the present study. Results. We have found that a person is capable to learn implicitly several patterns in structured information presented during the “sequence learning” task. There is no interference between different rules that were learned. Implicit knowledge about the pattern of relevant parameter has a major impact on solving the task that needs conscious control. Thereafter, learning the pattern of irrelevant parameter has no significant effect. Discussion and Conclusion. Learning of combined sequences can lead to positive and negative effects on further actions. Positive effect occurs when implicitly learned sequence corresponds to conditions of the task (relevant parameter remains). Negative effect occurs when sequence does not correspond to conditions of the task (relevant parameter changes). Positive and negative aftereffects of combined sequences learning can be interpreted as an expression of complex type setting phenomena: these effects occur because of unconscious state of readiness to perceive an appearance of objects in a certain way. The results can be useful for educational programme developers, especially in trai ning to use different kind of interfaces.

The paper is devoted to the study of the verbal semantic parameters used in the Russian National Corpus (RNC). The author analyzes the lexical-semantic groups of verbs and the problems of creating filters for automatically searching for a selected group (so-called secondary imperfectives). A detailed analysis of the corpus results revealed the problem with the semantic annotation of the RNC and the need for its improvement. Настоящая статья посвящена семантическим параметрам, используемым при поиске глаголов в Национальном корпусе русского языка (НКРЯ). Автор анализирует лексикально-семантическую группу глаголов и проблемы образования фильтров, применяемых к автоматическому поиску особенной группы глаголов (так наз. вторичных имперфективов). Анализ их семантического описания указывает на существенные недостатки НКРЯ и необходимость усовершенствования семантической разметки.

The paper proposes the new approach to educational text selection for the humanities teaching. Its specifics is based on the wide interpretation of educational texts, as the culture texts involved in cognitive learning activity and fulfilling the multiple tasks of the related subjects and personal development. The educational text is taken as a generalized model, its content and structure determining the scheme of a speech cognitive activity, as well as the meaning formation mechanism responsible for understanding and personal development. The texts and tasks selection is oriented on schoolchildren’s understanding with the reference to the psycholinguistic, psychological and hermeneutic approaches; information extraction and interpretation level related to the author’s and student’s context. The given approach could provide the basis for developing and structuring the textbooks content for the humanities subjects.

Working vocabulary of features include most informative features of objects to be recognized. The aim is to develop a method of forming a working vocabulary of features for recognition algorithms based on Fourier-descriptors of the object image contours.To solve this problem the paper offers to use the method of functional maximization that is the ratio of the distance between the classes to the spread of objects within each of the classes represented in the feature space, which is formed on the basis of Fourier-descriptors.To check the effectiveness of the proposed method to form a working vocabulary of features the numerical experiments have been carried out. The experiments used two databases of reference images consisting of 10 and 13 reference images. Test images obtained by rotating the reference images, by zooming, as well as by adding the noise using the normal law of distribution have been created from these images. The proposed by the author algorithm, which uses the Prewitt operator, threshold segmentation, and morphological processing has marked the contours of images. The original vocabulary of features derived from the Fourier-descriptors has dimension of 98. The vocabularies of working features having the dimensions, respectively, 3 and 4 have been formed on the basis of functional maximization for both reference images. In the course of numerical experiments the frequency of correct decisions to recognise the features of reference bases of images for the original and working vocabularies has been evaluated. It has been proved that the algorithm of recognition with the formed working vocabularies of features provides a great efficiency of automatic recognition of objects.There are known publications, which use a similar method to form a working vocabulary of features in algorithms of human recognition by the image. But there are no publications on choosing the vocabulary of features for recognition algorithms based on the analysis of the image contours that can be used in computer vision systems of automated production lines.

In this paper, a frame-based description of verbal polysemy is used to answer some questions concerning syntactic behavior and argument structures associated with complex predicates in Persian. In Persian a number of CPs consisting of a light verb (LV) and a preverb (PV) participate in causative alternation. The causative variant is formed with the LV ændaxtæn 'cause to fall' and the anti-causative variant is formed with oftadæn 'fall'. In some contexts these verbs do not participate in causative alternatioin. In other words they do not have an anti-causative variant in such contexts. The peculiar behavior of these verbs in different contexts is explained in the framework of Frame Semantics [2]. I will argue that these verbs are associated with two semantic frames and just one of them is compatible with both causative and antiicausative form. The other frame is compatible with causative form but incompatibel with anticausative form hence no anticausative variant. As for the A-structure of CPs, using the notion of Frames [5] it is proposed that the whole construction including the CP determines its A-structure. It is not detrmined just by PV [9] or compositionally by PV and LV [6].

The paper addresses the issues of diachronic description genetically related vocabulary East Slavonic languages based on a study of its origin and semantics in accordance with the actual problems of the historical word formation lexicology and lexicography Slavonic languages. To study involved pre-Slavic vocabulary, of ancient and modern East languages, united in the genetic paradigm, which consists of etymological families with vertices *Dati, *Bьrati, *Imati//Imѣti, *Nesti. В статье затрагиваются вопросы диахронического описания генетически близкой лексики восточнославянских языков на основе исследования её происхождения и семантики в соответствии с актуальными проблемами исторической дериватологии, лексикологии и лексикографии славянских языков.

Представлены результаты экспериментов по добавлению биграмм в тематические модели и учету сходства между ними и униграммами. Предложен новый алгоритм PLSA-SIM, являющийся модификацией алгоритма построения тематических моделей PLSA (Probabilistic Latent Semantic Analysis). Предложенный алгоритм позволяет добавлять биграммы и учитывать сходство между ними и униграммными компонентами. Исследована возможность применения ассоциативных мер для выбора и последующего включения биграмм в тематические модели. В качестве текстовых коллекций взяты русскоязычная подборка статей из электронных банковских журналов, английские части корпусов параллельных текстов Europarl и JRC-Acquiz и англоязычный архив исследовательских работ по компьютерной лингвистике ACL Anthology. Выполненные эксперименты показывают, что существует подгруппа тестируемых мер, упорядочивающих биграммы таким образом, что при последующем их добавлении в предложенный алгоритм PLSA-SIM качество получающихся тематических моделей значительно повышается. Предложен новый итеративный алгоритм PLSA-ITER без учителя, позволяющий добавлять наиболее подходящие биграммы. Эксперименты показывают дальнейшее улучшение качества тематических моделей по сравнению с исходным алгоритмом PLSA., The results of experimental study of adding bigrams and taking account of the similarity between them and unigrams are discussed. A novel PLSA-SIM algorithm based on a modification of the original PLSA (Probabilistic Latent Semantic Analysis) algorithm is proposed. The proposed algorithm incorporates bigrams and takes into account the similarity between them and unigram components. Various word association measures are analyzed to integrate top-ranked bigrams into topic models. As target text collections, articles from various Russian electronic banking magazines, English parts of parallel corpora Europarl and JRC-Acquiz, and the English digital archive of research papers in computational linguistics (ACL Anthology) are chosen. The computational experiments show that there exists a subgroup of tested measures that produce top-ranked bigrams in such a way that their inclusion into the PLSA-SIM algorithm significantly improves the quality of topic models for all collections. A novel unsupervised iterative algorithm named PLSA-ITER is also proposed for adding the most relevant bigrams. The computational experiments show a further improvement in the quality of topic models compared to the PLSA algorithm., ВЫЧИСЛИТЕЛЬНЫЕ МЕТОДЫ И ПРОГРАММИРОВАНИЕ: НОВЫЕ ВЫЧИСЛИТЕЛЬНЫЕ ТЕХНОЛОГИИ, Выпуск 2 2015

The paper represents main ideas of my theory “Relative verity logic” (RVL), that combines advantages of two contrary approaches to vagueness (many-valued theory and supervaluationism). RVL allows the fruitful treatment of borderline cases while saving all the classical tautologies and inference rules; and on top of all this, it also avoids the trap of the sorites paradoxes., В статье излагаются основные идеи разработанной автором теории относительной истинности для расплывчатых предикатов «Relative verity logic» (RVL), которая представляет попытку соединить преимущества двух противоположных подходов к проблеме расплывчатости (многозначного и сверхоценочного). RVL предлагает продуктивный анализ пограничных предложений, при этом сохраняет все классические тавтологии и правила вывода и позволяет избежать «парадокса кучи»., Осмислюються основні ідеї розробленої автором теорії відносної істинності для розмитих предикатів «Relative verity logic» (RVL). Теорія є спробою поєднати переваги двох протилежних підходів до проблеми розмитості (багатозначного і надоціночного). RVL пропонує продуктивний аналіз граничних речень, при цьому зберігає всі класичні тавтології і правила виведення, дозволяє уникнути «парадоксу купи».

The paper considers issues of formal methods in the tasks of knowledge representation including optimization of formal grammars by means of functional programming languages. One of the possible applications of the formal notation given is illustrated by the task of parallel natural texts analysis and comparison.