The goals of the study were the formation of a model of concentrated plasticity based on spherical graphite fibers. The goal was to present indicators of the cyclic behavior of structural elements due to the lack of consideration in modern scientific research of the issue of increasing the technical level and reliability of structures due to the addition of innovative materials during the development of structural elements. Taking into account the fundamental shortcomings in construction in the conditions of installing an excess amount of reinforcement, as one of the main mechanisms for achieving strength and reliability. The aim of the study was to develop a method of improving the quality of structural elements using innovative materials through building spring hinge models. The study involved the mathematical simulation, comparison, and system analysis. The result of the work is a developed spring hinge model for simulating reinforced concrete structural elements. The work emphasizes that the obtained experimental model converges to reference data and does not reflect a significant error with the increased number of cycles. It is emphasized that the model degrades with significant calibration, while the numerical strength and hysteresis behaviour matches the experimental data at higher deformation levels. The model of concentrated plasticity based on spherical graphite fibers was developed for the range of indicators of the cyclic behaviour of structural elements. The main characteristics of the reinforced concrete structural elements under consideration in the framework of the study are provided in a table in order to visually separate the groups of structures according to the main parameters. A non-linear model of a spring hinge is graphically shown, which shows the moment of movement of the spring when a monotonous load is applied. An urgent need to build a system of indicators of the structural elements’ cyclic behaviour was emphasized. A concentrated plasticity model based on spherical graphite fibers was built for this purpose. A beam-column was chosen as a reinforced concrete structure, which is based on a zero-length spring pivot hinge at the end of each individual element. This spring pivot hinge is a uniaxial material model with a moment-rotation dependency. Such a dependency is the fundamental basis of the spring hinge model used to simulate reinforced concrete structural elements. The comparison chart of reference and cyclic strength of a spherical graphite reinforced concrete beam is presented graphically. Prospects for further research involve the development of an empirical system of equations depending on the section geometry and the properties of the structure material based on prognostic variables from the list of potential variable characteristics.
Розроблено методи автоматичного аналізу тексту на основі декларативного представлення правил синтаксичної сполучуваності та програмного розподілення аналітико-синтетичної обробки природно-мовного тексту в системах машинного перекладу. Програмна реалізація експерементально доводить, що застосування розроблених методів зменшує кількість помилок семантичного характеру в середньому на 14-16 % у порівнянні з відомими системами машинного перекладу Ключові слова: система машиного перекладу, автоматичний аналіз тексту, аналітико-синтетична обробка тексту Разработаны методы автоматического анализа текста на основе декларативного представления правил синтаксической соединяемости и программного распределения аналитико-синтетической обработки естественно-языкового текста в системах машинного перевода. Програмная реализация експерементально подтверждает, что применение разработанных методов уменьшает количество ошибок семантического характера в среднем на 14-16 % по сравнению с известными системами машинного перевода Ключевые слова: система машинного перевода, автоматический анализ текста, аналитико-синтетической обработка текста
Today, more and more information is being accumulated in digital form, including media content, which is a growing segment of the Internet, searching for such content is an important task, but it is significantly different from textual information search and involves image recognition. Images recognition is an automatic comparison of images to objects in a class. There are two major issues in this area: classification and identification. The first helps the search engine to understand what type of object is in the media resource. Only correctly having solved this fundamental problem, the computer will be able to distinguish, for example, a dog from a cat. The second allows not only to find the object category, but also to identify it. The article defines the mathematical formulation of the problem, which is important in order to formalize the accuracy of recognition and to determine the procedure for comparing the capabilities of existing algorithms. The results show that existing APIs allow you to largely solve the problem of face recognition in images, and the next important step is to recognize the face of a person on the move, that is, on video content.
Abstract. The article describes the approach to semantics coding developed by the author and aimed for systems of natural language text information automatic processing. The offered method is based on positional-digital coding of semantic information that is assigned to words or phrases in text. The feature of semantic digital code is its genericity and excessiveness that shows in intersection of lexical-grammatical and lexical-semantic information; this allows adequate processing of different language texts in conditions of polysemy and indetermination. Keywords: semantic code, lexical units, natural language automatic processing, semantic features IntroductionToday building of a formal model for text's semantics is the weakest link in systems of natural language texts (NLT) automatic processing. Though developments in this trend have been performed for a long time, there are no any established universal methods for text's content analysis. (Marchuk, 2007) conditionally divides researches in branch of semantics formalization into two directions:researches that are hold on deductive abstract-theoretical level, the aim of which is to set a correlation between semantics and semiotics from one side, semantics and syntactics and pragmatics from the other one; build models for NLT comprehension in general and in relation to communication process; research of inductive empirical character, its aim is to solving definite applied problems: machine translation, automatic information search, annotation etc.The other direction bears fragmentary character, methods that are developed on definite system, not suitable for solving other problems.The first direction has fundamental character, and results received within this research would allow the applied research direction to be deprived of its defects.Within this direction the most famous models today are the universal semantic code (USC), developed under supervision of Martynov (1984)and model of lexical semantics of Y. Apresyan that formed the base for model "SENSE-TEXT".The USC model provides functional or thematic approach, i.e. items are reviewed only in interaction within a sentence. Kernel sentence structure appears as content unit that is formally written down by formula: S whereS -subject, A -action, O -addition. A O The sentence is firstly divided into elementary links and then it is connected to an integral phrase due to formal operations. In fact the USC is a transformation from syntactic sentence structure to semantic one. The main disadvantage of this model is that we need a definitely marked sentence syntactic structure that is an unachievable condition at automatic syntactic NLT analysis. Besides this, the present model does not provide lexical semantics that in fact is the base for solving syntactical ambiguity.The other model is based on a hypothesis that an expression (sentence) has a sense just when lexical items that are part of a sentence have common significance particles (semes). On that basis, every word (established collocation) is described by a s...
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