Abstract: This study discusses some of the shortcomings of Gaussian humanization and discusses how the articulation models developed by drummers can be emulated using a probabilistic model. An author's algorithm for “revitalizing” midi-parts of percussion instruments was developed. Various dependencies and regularities, which are manifested when playing drums, are programmed. The dependence of the notes parameters not only on the parameters of the previous notes, but also on the subsequent notes of the corresponding parts of the drum set was created. The dependence of the impact force on the position of the note in the measure is created. Thus, emphasizing notes in a strong lobe. Also, the dependence of the note's volume on the coincidence with the notes of other parts of the drum set was created. To increase the dynamism and liveliness of the party, the volume of the hat was increased before the impact on the small drum. A comparison was made of the amplitudes of the corresponding notes of the parts, as far as the party, animated using a certain method, is different from the one played by a professional drummer. When listening to tests, batches processed using a modified method objectively sound lively than using Gaussian and quantized batches.

Abstract:

In this paper, we study the possibility of using Finite State Machine (FSM-) based methods for deriving finite test suites with guaranteed fault coverage for Input / Output automata. A method for deriving an FSM for a given automaton is proposed and it is shown that finite test suites derived for such an FSM are complete for two fault models based on Input/Output automata if they are applied within the framework of proper timeouts.

Abstract:

he ontology-based approach to multi-agent modeling involves the implementation of a modeling system through the creation of ontologies. An example of a holistic implementation of an ontology-based approach to agent-based modeling is the IEEE 1516 Standard for Modeling and Simulation High Level Architecture. The work is devoted to a multi-agent modeling system designed for modeling complex radio engineering systems (especially radar systems), its relevance is due to the need to replace part of the field tests of radio engineering systems with simulation experiments. The motivation for switching to the IEEE 1516 standard for a "heavy" multi-agent modeling system, among other things, is to ensure scalability, openness and multiple reuse of the developed agent models, which is completely logical to do based on the existing well-developed and proven standard that establishes rules for the interaction of models and the development of software interfaces. The general principles of construction and architecture of the modeling system are given. The basic requirements for the main modeling agents, their role and place in the complex modeling system are shown, a special place among which is occupied by the simulator of the background-target environment. The possibility of combining two simulation schemes is also discussed: discrete-event and step-by-step. The fact is that the step-by-step scheme has advantages such as simplicity and clarity, it is convenient to model processing algorithms, components of radio engineering systems. However, it is impossible to implement true autonomy and asynchrony of agents in it. Combining two modeling schemes allows you to combine their advantages.

Abstract:

The article is dedicated to the experience of the Russian State Library (RSL) in testing research papers for incorrect borrowings. Relevant digital collection of research papers, specialized software and expert analysis are regarded as necessary components for such tests being carried out. The article describes their main results, as well as the most common flaws found in the research papers tested.

Abstract:

In the context of digital transformation of organizations and the growing volume of data, there is a demand for more transparent and explainable approaches to employee evaluation. The purpose of the study is to design and validate an ontological model (OWL 2/SHACL) that integrates employees’ cognitive indicators and sociological characteristics into a unified knowledge space to support HR processes. The scientific novelty of the work lies in the development of a unified semantic model linking data from cognitive tests, questionnaires, work context, and performance indicators; in the formulation of competency questions (CQ) that trigger reasoning mechanisms within the knowledge graph; and in the creation of patterns for predicting competency gaps, identifying the risk of overload/burnout, while ensuring ethics and non-discrimination control. The proposed approach is based on ontology engineering methodologies – METHONTOLOGY and NeOn, semantic web concepts, and psychometric methods.

Abstract:

The results of studies of atmospheric pressure in the Arctic region of Russia in the period from 1948 to 2008 are presented. The analysis of the climatic seasonal variation of the atmospheric pressure fields is carried out. As the main research method, the probabilistic and statistical analysis of the time series of the pressure field 60 years long at fixed points in the region of the Arctic zone of Russia was used. In total, about 90,000 daily (in six-hour increments) pressure values were examined. On the basis of these data, a climatic seasonal variation was constructed as an averaging of the values of a given time series at each point in space and for a fixed date. The characteristics of the seasonal course, its amplitude and phase have been studied. These characteristics were analyzed and their geophysical interpretation was carried out. In particular, the minimum and maximum values ​​of the series were determined for the entire region and the time series of these characteristics were constructed. It is shown that the deviation is asymmetric, this is an unobvious research result. For the maximum and minimum, the best approximations were constructed, and these approximations were tested by known methods of statistical analysis, including maximum likelihood, least squares and goodness of fit methods (tests), in particular, the χ²-criterion. The conducted research has applications both purely physical (allows to explain the nature, genesis and distribution of large-scale atmospheric formations in a climatic year) and prognostic (allows understanding and tracking trends in climate, as well as quantitatively assessing the scale and variability of large-scale atmospheric processes). Numerical calculations were performed on the Lomonosov-2 supercomputer of the Lomonosov Moscow State University.

Abstract:

An analysis of the speed and efficiency of data transfer using the WebSocket and REST API protocols was carried out. To compare the speed of processing stream objects and identify a more reliable technology for developing APIs, expansions of basic functions in Taylor and Fourier series were used. As a result, it was revealed that the REST API is a faster and more accessible resource for transmitting information data in a bitwise transformation, and the scalability of this protocol prevails in the number of processed units, which allows expanding the number of tests performed.

Abstract:

Translated plagiarism has widely spread in a scientific world and posed a serious problem due to the challenges in its automatic detection. However, in the last five years some progress has been observed in this area. The authors of this paper, as well as foreign research team from several universities independently of each other proposed an approach to detect plagiarism based on citation analysis with search of initial source for analyzed suspected paper with the same or similar references. Developed methods of detection of illegal use of borrowed text successfully passed several tests. The report shows the results that we have obtained in the last four years.

Abstract:

Large Language Models (LLMs) have evolved from simple n-gram systems to modern universal architectures; however, a key limitation remains the quadratic complexity of the self-attention mechanism with respect to input sequence length. This significantly increases memory consumption and computational costs, and with the emergence of tasks requiring extremely long contexts, creates the need for new architectural solutions. Since evaluating a proposed architecture typically requires long and expensive full-scale training, it is necessary to develop a tool that allows for a rapid preliminary assessment of a model’s internal memory capacity.

This paper presents a method for quantitative evaluation of the internal memory of neural network architectures based on synthetic tests that do not require large data corpora. Internal memory is defined as the amount of information a model can reproduce without direct access to its original inputs.

To validate the approach, a software framework was developed and tested on the GPT-2 and Mamba architectures. The experiments employed copy, inversion, and associative retrieval tasks. Comparison of prediction accuracy, error distribution, and computational cost enables a fast assessment of the efficiency and potential of various LLM architectures.

Abstract:

Steel is one of the most important bulk materials these days. It is used almost everywhere - from medicine to industry. Detecting this material's defects is one of the most challenging problems for industries worldwide. This process is also manual and time-consuming. Through this study we tried to automate this process. A convolutional neural network model UNet was used for this task for more accurate segmentation with less training image data set for our model. The essence of this NN (neural network) is in step-by-step convolution of every image (encoding) and then stretching them to initial resolution, consequently getting a mask of an image with various classes on it. The foremost modification is changing an input image's size to 128x800 px resolution (original images in dataset are 256x1600 px) because of GPU memory size's limitation. Secondly, we used ResNet34 CNN (convolutional neural network) as encoder, which was pre-trained on ImageNet1000 dataset with modified output layer - it shows 4 layers instead of 34. After running tests of this model, we obtained 92.7% accuracy using images of hot-rolled steel sheets.

Abstract:

This article presents elements of the linguistic knowledge graph “Turklang”, developed at the Institute of Applied Semiotics of the Academy of Sciences of Tatarstan and used as a basis for creating a number of linguistic resources and tools: the portal “Turkic Morpheme”, the electronic corpus of the Tatar language “Tugan Tel”, morphoanalyzer. Creating an educational environment requires subject-oriented knowledge graphs, for which methods of general and open graphs are not suitable. This paper describes linguistic knowledge graphs, which reflect, on the one hand, potential capabilities of Turkic languages, and on the other hand, examples of actual use in texts. Peculiarity of these knowledge graphs is that they contain linguistic units of different linguistic levels, and concepts corresponding to meanings of these linguistic units, which are built into the thesaurus of concepts. Structure of this knowledge graph allows to formulate the content of a training course, build an individual educational trajectory, as well as create tests and tools of automated answer grading as part of knowledge control when teaching Turkic languages. This makes it possible to subsequently develop, based on these graphs, training programs taking into account the structural and functional features of the Turkic languages, and also contributes to the implementation of individual goals of students.

Abstract:

An approach for designing Microlearning Applications is presented. The dependency of reliability of knowledge evaluation from visual representation of testing questions. And architecture of system and working principle of developed instrument for designing adaptive tests and testing scenarios is shown.

Abstract:

A solution for the problem of testing controllers based on reading information from their screens is described. A hardware and software system has been developed for this purpose, consisting of a camera and software modules implementing the necessary algorithms and methods: an image preprocessing module; a menu type detection module; a font character processing module; a text reading module, including one written in various fonts; and the testing module itself. The system has been developed for a specific type of controller with a monochrome 128x64 pixel display. All methods are implemented in Python using popular libraries. The system has been launched into test operation and currently automates several of the most labor-intensive tests. The test set can be expanded using plugins.

Abstract: When deriving tests for checking functional and nonfunctional requirements for components of control systems, the notion of separablity becomes very important that is used for distinguishing the fault-free component from a faulty one. In order to do this, proper separating sequences are utilized. Such sequences are well studied for complete and deterministic Finite State Machines but components of control systems can be only partially described and their behavior can be nondeterministic. In this paper, we consider the formal model of Input/Output automata, introduce the notion of a separating sequence for two such automata and propose an approach for deriving such a separating sequence.

Abstract:

The paper is devoted to the study of the cognitive function associated with the generation of elliptical sentences in the Russian language. The study is conducted by testing this cognitive ability using a computer system specially developed by the authors for this purpose. Testing of this cognitive ability is proposed and implemented for the first time. The system is an extension of Moodle and is openly hosted in the github repository. Elliptical constructions are limited to verbal and nominal ellipses, which are theoretically possible to be completely reconstructed based on the context of the sentence. The study is conducted with the participation of SPbPU students as respondents. The texts of planimetric tasks are chosen as the subject area. As a result of the analysis of testing data, the following results are obtained: the influence of the respondent’s knowledge of the subject area (planimetry) on the test results is established; a tendency towards self-study of respondents was discovered, which is manifested in a reduction in time and an increase in scores as they pass tests; it is shown that respondents are poorly motivated if they do not see feedback on the answer to the completed task. The paper discusses the problems of further development of the testing system and its use in adapting questionnaires (tasks) to assess the knowledge of SPbPU students in the field of automation of bug detection in programs, as well as for diagnosing the functional state of operator specialists and express diagnosis of dementia. It also seems promising to use the system to improve the processes of syntactic parsing of elliptic sentences and automate the restoration of ellipses in the subject area of planimetry.

Abstract: The problem of sorting data is analyzed, the order relation between which is described as the adjacency relation of vertices on an arbitrary graph. Subtasks and issues related to the ‘neighborhood‘ of the problem are highlighted; their solution is the level of ‘immersion‘ in the solution of the general problem. Algorithms for solving individual subtasks for graphs of a special kind are discussed, as well as various approaches to solving the sorting problem in the general case. A sorting task of this type was proposed at the ISI-Junior School Programming Cup in July 2019 (Innopolis).

Abstract:

Methods of kernel estimation of a priori density in the deconvolution problem are used to construct guaranteed procedures for distinguishing between two one-sided hypotheses. The situation is considered when the observed random variable is the sum of an unknown parameter and a centered normal error with a known variance. Consistent empirical estimates are constructed for the d-posterior risk function. The convergence of the corresponding critical constant to the optimal value is established. The accuracy of the procedures is illustrated numerically on three variants of the prior distribution.

Abstract: The system for automated parallelization SAPFOR (System FOR Automated Parallelization) includes tools for program analysis and transformation. The main goal of the system is to reduce the complexity of program parallelization. SAPFOR system is focused on the investigation of multilingual applications in Fortran and C programming languages. The low-level LLVM IR representation is used in SAPFOR for program analysis. This representation allows us to perform various IR-level optimizations to improve the quality of program analysis. At the same time, it loses some features of the program, which are available in its higher level representation. One of these features is the multi-dimensional structure of the arrays. Data dependence analysis is one of the main problems which should be solved to automate program parallelization. Moreover, such an analysis belongs to the class of NP-hard problems. Knowledge of the multidimensional structure of arrays allows in many cases to take into account the structure of index expressions in calls to arrays and reduce the complexity of the analysis. In addition, the use of multi-dimensional arrays allows us to use multi-dimensional processor matrix and to parallelize a whole loop nests, rather than a single loop in the nest. So, parallelism of a program is going to be increased. These opportunities are natively supported in the DVM system. This paper discusses the approach used in the SAPFOR system to recover the form of multi-dimensional arrays by their linearized representation in LLVM IR. The proposed approach has been successfully evaluated on various applications including performance tests from the NAS Parallel Benchmarks suite.

Abstract:

The article describes the experience of digital transformation of mathematical disciplines based on author's digital educational platform Mirera. The Mirera DEP is optimized for the Russian system of organization of higher education, focused on the development and delivery of courses that combine online and offline technologies for conducting the educational process. The Mirera DEP provides course authors with tools for developing computerized courses with automated verification of the correctness and independence of current and control tasks performed by students using artificial intelligence methods. Various original types of tests are built into the platform, supporting both in the description of tasks and in answer options, content in various formats, including TeX, sequences of elements (for automated testing of student knowledge of the structure of proof of course theorems or schemes for solving typical problems), semantic analysis of text responses, etc.

Abstract: An approach to automatically generating questions for tests or quizzes using the DBPedia knowledge graph is presented here. The selected knowledge graph has about 5 million entities. DBpedia SPARQL endpoint the ability to make queries to the semantic network using the SPARQL language. The algorithm, the basic queries to the knowledge graph for constructing questions, a non-standard approach to the search for entities are presented in this article.

Abstract: The use of pointers and indirect memory accesses in the program, as well as the complex control flow are some of the main weaknesses of the static analysis of programs. The program properties investigated by this analysis are too conservative to accurately describe program behavior and hence they prevent parallel execution of the program. The application of dynamic analysis allows us to expand the capabilities of semi-automatic parallelization. In the SAPFOR system (System FOR Automated Parallelization), a dynamic analysis tool has been implemented, based on on the instrumentation of the LLVM representation of an analyzed program, which allows the system to explore programs in both C and Fortran programming languages. The capabilities of the static analysis implemented in SAPFOR are used to reduce the overhead program execution, while maintaining the completeness of the analysis. The use of static analysis allows to reduce the number of analyzed memory accesses and to ignore scalar variables, which can be explored in a static way. The developed tool was tested on performance tests from the NAS Parallel Benchmarks package for C and Fortran languages. The implementation of dynamic analysis, in addition to traditional types of data dependencies (flow, anit, output), allows us to determine privitizable variables and a possibility of pipeline execution of loops. Together with the capabilities of DVM and OpenMP these greatly facilitates program parallelization and simplify insertion of the appropriate compiler directives.

Abstract:

This paper presents a critique of the traditional approach used to create a multiplayer game in the Unity real-time interactive application development system, especially in the case of a large number of concurrent users. As a hypothesis, an alternative option, which is not common, but which solves many of the problems of the previous approach, is proposed. Two client-server solutions have been compared for developing multiplayer online games in Unity, and the advantages of both approaches have been described for different cases. A game development architecture using a more up-to-date method is proposed: instead of the Mirror library, a standard toolkit for Unity development, microservices written in Golang are used. We present solid proofs of the preference of the alternative approach, the main advantage of which is the support of modern architecture providing high-speed communication between microservices, supported tests on messaging on different platforms.

The test results confirm the hypothesis put forth, and we can conclude that the Unity bundle with Golang is more effective for multiplayer video games.

The article also contains basic methods for debugging multi-threaded application in Golang bundled with Unity game development system and suggests a technological method that allows to get a fast way of data transfer between the client and the server.

Abstract:

The results on the creation of methods for managing mathematical knowledge in the context of digital mathematical libraries are presented. The software tools developed on the basis of these methods are part of the OntoMath digital ecosystem, within which they interact. A brief description of the architecture of the OntoMath ecosystem is given, the levels of subject ontologies and external ontologies are highlighted, as well as the level of software tools and services. Semantic services are separated into a separate category. This term denotes software tools, in the functionality of which queries to subject ontologies are used to ensure the management of knowledge objects. General descriptions of developed subject ontologies are given: educational mathematical ontology OntoMath^Edu and ontology of professional mathematics OntoMath^PRO. The development of educational ontology is reflected in the direction of including educational prerequisite links between classes. Among the software tools of the digital ecosystem, search services for mathematical electronic collections, a service for semantic annotation of mathematical documents, tools for semantic marking of educational mathematical documents, as well as a system for automatically generating testing tests in mathematical educational disciplines are highlighted. As part of the OntoMath digital ecosystem, special-purpose recommender systems are being developed. The current version of the ecosystem includes a recommender system for generating a list of related articles based on the OntoMath^PRO ontology, a recommender system for appointing experts to support the scientific review process, and recommender systems for selecting subject classifiers UDC and Mathematics Subject Classification codes for mathematical documents. The results are also presented in the direction of creating a digital library metadata factory, which includes services and tools for extracting, refining, replenishing and normalizing the metadata of electronic mathematical collections. Note that the OntoMath ecosystem is being developed as the technological basis for the Lobachevskii Digital Mathematical Library.