Search

Formal proof of security measure effectiveness and computation security is vitally important for trust in critical information systems. It should be realized that formal security verification must be carried out at each infrastructural level (from the hardware level to the application level) in the process of system design. Currently, computation security analysis on the application level remains the major challenge as it requires complex labeling of computing environment elements. Traditionally, to solve this problem, information flow control (IFC) methods are employed. Unlike access control mechanisms widely used in modern operating systems (OSs) and database management systems (DBMSs), IFC has limited application in software design and mostly comes down to trivial taint tracking. This paper describes an approach to full-fledged implementation of IFC in PL/SQL program units with the use of the PLIF platform. In addition, a general scheme of computation security analysis for enterprise applications that work with relational DBMSs is considered. The key advantage of our approach is the explicit separation of functions between software developers and security analysts. [ABSTRACT FROM AUTHOR]

This paper considers theoretical foundations and mathematical methods of data analysis under the conditions of the Rice statistical distribution. The problem involves joint estimation of the signal and noise parameters. It is shown that this estimation requires the solution of a complex system of essentially nonlinear equations with two unknown variables, which implies significant computational costs. This study is aimed at mathematical optimization of computer algebra methods for numerical solution of the problem of Rician data analysis. As a result of the optimization, the solution of the system of two nonlinear equations is reduced to the solution of one equation with one unknown variable, which significantly simplifies algorithms for the numerical solution of the problem, reduces the amount of necessary computational resources, and enables the use of advanced methods for parameter estimation in information systems with priority of real-time operation. Results of numerical experiments carried out using Wolfram Mathematica confirm the effectiveness of the developed methods for two-parameter analysis of Rician data. The data analysis methods considered in this paper are useful for solving many scientific and applied problems that involve analysis of data described by the Rice statistical model. [ABSTRACT FROM AUTHOR]

His main interests include resource optimization technique, adaptive resource provisioning, multi-objective optimization, computational intelligence, incomplete information processing, cloud computing, and security. The evaluation showed that these apps had an acceptable score on the System Usability Scale (SUS). The paper "Influence of Belbin's Role Theory on Database Design: Experimenting with Software Engineering Students" explores the benefits of using Belbin's role theory of team and individual related tasks in the software development process, particularly for Database Design (DB) Design. The authors argued that the usability evaluation described in this work can serve as a reference for developers seeking to improve learning monitoring and personalization services in software applications. [Extracted from the article]

Segmentation of whole slide histological images through the classification of tissue types of small fragments is an extremely relevant task in digital pathology, necessary for the development of methods for automatic analysis of whole slide histological images. The extremely large resolution of such images also makes the task of increasing image resolution relevant, which allows storing images at a reduced resolution and increasing it if necessary. Annotating whole slide images by histologists is complex and time-consuming, so it is important to make the most efficient use of the available data, both labeled and unlabeled. In this paper we propose a novel neural network method to simultaneously solve the problems of super-resolution of histological images from ×20 optical magnification to ×40 and classifying image fragments into tissue types at ×20 magnification. The use of a single encoder as well as the proposed neural network training scheme allows to achieve better results on both tasks compared to existing approaches. The PATH-DT-MSU WSS2v2 dataset presented for the first time in this paper was used for training and testing the method. On the test sample, an accuracy value of 0.971 and a balanced accuracy value of 0.916 were achieved in the classification task on 5 tissue types, for the super-resolution task, values of PSNR = 32.26 and SSIM = 0.89 were achieved. The source code of the proposed method is available at: https://github.com/Kukty/WSI_SR_CL. [ABSTRACT FROM AUTHOR]

Currently, the digitization of environment objects (vegetation, terrain, architectural structures, etc.) in the form of point clouds is actively being developed. The integration of such digitized objects into virtual environment systems allows the quality of the modeled environment to be improved, but requires efficient methods and algorithms for real-time visualization of large point volumes. In this paper the solution of this task on modern multicore GPUs with support of hardware-accelerated ray tracing is researched. A modified method is proposed where the original unordered point cloud is split up into point groups whose visualization is effectively parallelized on ray tracing cores. The paper describes an algorithm for constructing such groups using swapping arrays of point indices, which works faster than alternative solutions based on linked lists, and also has lower memory overhead. The proposed method and algorithm were implemented in point cloud visualization software complex and approbated on a number of digitized environment objects. The results of the approbation confirmed the efficiency of proposed solutions as well as their applicability for virtual environment systems, video simulators, geoinformation systems, virtual laboratories, etc. [ABSTRACT FROM AUTHOR]

In this paper we consider the problem of detecting blurred regions in high-resolution whole slide histologic images. The proposed method is based on the use of a Fourier neural operator trained on the results of two simultaneously used approaches: blur detection using multiscale analysis of the discrete cosine transform coefficients and estimation of the degree of sharpness of objects edges in the image. The efficiency of the algorithm is confirmed on images from the datasets PATH-DT-MSU [1] and FocusPath [2]. [ABSTRACT FROM AUTHOR]

This document is a guest editorial for a special issue of the journal "Programming & Computer Software" titled "Recent Trends on Advanced Computing: The Converging Technologies." The issue features research and practical implementation results from researchers and industry experts in computer science, engineering, and technology. The papers cover a range of topics including microservices, software quality, user engagement on social media, non-functional requirements, medical software architecture, fallacies in political speeches, intelligent learning environments, and more. The guest editors for this special issue are Prof. Dr. Andrei Tchernykh, Prof. Reyes Juárez Ramírez, Dr. Esteban Mocskos, and Prof. Sergio Nesmachnow. [Extracted from the article]

The restoration of blurred images is a crucial topic in the field of machine vision, with far-reaching implications for enhancing information acquisition quality, improving algorithmic accuracy and enriching image texture. Efforts to mitigate the phenomenon of blur have progressed from statistical approaches to those utilizing deep learning techniques. In this paper, we propose a Generative Adversarial Network (GAN)-based image restoration method to address the limitations of existing techniques in restoring color and detail in motion-blurred images. To reduce the computational complexity of generative adversarial networks and the vanishing gradient during learning, an U-net-based generator is used, and it is configured to emphasize the channel and spatial characteristics of the original information through a proposed CSAR(Channel and Spatial Attention Residual) blocks module rather than a simple concatenate operation. To validate the efficacy of the algorithm, comprehensive comparative experiments have been conducted on the GoPro dataset. Experimental results show that the peak signal-to-noise ratio is improved compared to SRN and MPRNet algorithms with good image restoration ability. Objects detection experiments using Yolo V3 showed that the proposed algorithms can generate deblerring images with higher information quality. [ABSTRACT FROM AUTHOR]

In this paper, we continue to consider the problem of recovering the port-Hamiltonian structure for an arbitrary system of differential equations. We complement our previous study on this topic by explaining the choice of machine learning algorithms and discussing some details of their application. We also consider the possibility provided by this approach for a potentially new definition of canonical forms and classification of systems of differential equations. [ABSTRACT FROM AUTHOR]

The article offers information on the PSI'11 conference, dedicated to Russian scientist and academician Andrei Ershov, to be held on June 27 to July 1, 2011 in Novosibirsk, Akademgorodok, Russia.

This paper reviews the literature on automatic code generation of user-centered serious games. We decided to break the study in two parts: one study about serious games with model driven engineering, and another study about user-centered serious games. This paper presents an extension of a paper presented at CONISOFT 20 where a systematic review of 5 years old at the time of writing was presented exclusively. The systematic literature review conducted in this paper covers a decade of information from January 2012 to June 2022. The main objective is to know the literature that helps to mitigate the costs and time of software development in serious games. The overall conclusion is that there is still work to be done to combine serious user-centered games and automatic generation. This paper is a systematic review that identifies relevant publications and provides an overview of research areas and publication venues. In addition, Research perspectives were classified according to common objectives, techniques, and approaches. Finally, is presented point out challenges and opportunities for future research and development. [ABSTRACT FROM AUTHOR]

The technologies of artificial intelligence and cloud computing systems have recently been actively developed and implemented. In this regard, the issue of their joint use, which has been topical for several years, has become more acute. The problem of data privacy preservation in cloud computing acquired the status of critical long before the necessity of their joint use with artificial intelligence, which made it even more complicated. This paper presents an overview of both the artificial intelligence and cloud computing techniques themselves, as well as methods to ensure data privacy. The review considers methods that utilize differentiated privacy; secret sharing schemes; homomorphic encryption; and hybrid methods. The conducted research has shown that each considered method has its pros and cons outlined in the paper, but there is no universal solution. It was found that theoretical models of hybrid methods based on secret sharing schemes and fully homomorphic encryption can significantly improve the confidentiality of data processing using artificial intelligence. [ABSTRACT FROM AUTHOR]

Instrument panels of modern aircrafts are created based on the concept of glass cockpit. This new interface philosophy improves the perception of important flight information by displaying it on a single multi-function display. This paper considers problems that arise when developing a certified cockpit display visualization system designed for operation on civil aircrafts under the Russian real-time operating system JetOS. The paper presents several algorithmic solutions that make it possible to achieve acceptable rendering speed. In particular, a solution to the problem of rigid scheduling of operating system partitions is described in detail. This solution makes it possible to overcome the degradation of rendering speed. Some directions for further research are outlined. [ABSTRACT FROM AUTHOR]

This scientific paper explores the operation of a multiprocessor task servicing system. Tasks are received into the system at random intervals and are characterized by several stochastic parameters, including the number of processors required for their execution, the maximum allowable busy time for these processors, and the permissible waiting time in the task queue. The organization of task servicing in this system follows a first-in, first-out (FIFO) approach, ensuring uninterrupted processing. The key servicing process involves periodically selecting the first task in the queue and assessing its feasibility for immediate execution. If the task meets the necessary criteria, it is dispatched for processing. This process continues iteratively until a task is found, the parameters of which prevent immediate servicing. It is important to note that tasks in the queue have a limited window of time within which they can be serviced; otherwise, they may exit the system without service. This paper focuses on systems characterized by exponential distributions for random variables related to task arrivals, servicing times, and waiting restrictions. A system of equations is derived that describes the system's steady-state behavior. These equations enable the calculation of probabilities associated with the system's various states. Additionally, the paper provides insights into the probability distributions of virtual waiting times for tasks that arrive in the system at any given moment. [ABSTRACT FROM AUTHOR]

Quantum computing is based on the principles of quantum mechanics, such as superposition, entanglement, measurement, and decoherence. The basic units of computation are qubits, which are abstract objects with a mathematical expression to implement the quantum mechanics principles. Alongside quantum hardware, software is a principal element for conducting quantum computing. The software consists of logic gates and quantum circuits that implement algorithms for the execution of quantum programs. Due to those characteristics, quantum computing is a paradigm that non-physics experts cannot understand. Under this new scheme for developing software, it is important to integrate a conceptual framework of the fundamentals on which quantum computing is based. In this paper, we present a kind of taxonomical view of the fundamental concepts of quantum computing and the derived concepts that integrate the emerging discipline of quantum software engineering. We performed a quasi-systematic mapping for conducting the systematic review because the objective of the review only intends to detect the fundamental concepts of quantum computing and quantum software. The results can help computer science students and professors as a starting point to address the study of this discipline. [ABSTRACT FROM AUTHOR]

The field of human event recognition using visual data in smart environments has emerged as a fruitful and successful area of study, with extensive research and development efforts driving significant advancements. These advancements have not only provided valuable insights, but also led to practical applications in various domains. In this context, human actions, activities, interactions, and behaviors can all be considered as events of interest in smart environments. However, when it comes to smart classrooms, there is a lack of unified consensus on the definition of the term "human event." This lack of agreement presents a significant challenge for educators, researchers, and developers, as it hampers their ability to precisely identify and classify the specific situations that are relevant within the educational context. The aim of this paper is to address this challenge by conducting a systematic literature review of relevant events in smart classrooms, with a focus on their applications in assistive technology. The review encompasses a comprehensive analysis of 227 published documents spanning from 2012 to 2022. It delves into key algorithms, methodologies, and applications of vision-based event recognition in smart environments. As the primary outcome, the review identifies the most significant events, classifying them according to single person behavior, or multiple-person interactions, or object-person interactions. It also examines their practical applications within the educational context. The paper concludes with a discussion on the relevance and practicality of vision-based human event recognition in smart classrooms, particularly in the post-COVID era. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the effectiveness of classical approaches to active learning in the problem of document segmentation with the aim of reducing the size of the training sample. A modified approach to selection of document images for labeling and subsequent model training is presented. The results of active learning are compared to those of transfer learning on fully labeled data. The paper also investigates how the problem domain of a training set, on which a model is initialized for transfer learning, affects the subsequent uptraining of the model. [ABSTRACT FROM AUTHOR]

In this paper, based on height field surface example, an efficient technology of real-time modeling of complex procedural objects on the ray tracing pipeline (RT-pipeline) is proposed. The proposed technology doesn't overload the I-shader stage (intersection shader), but distributes the computational load between the I-shader and the AH-shader (any-hit shader). The key innovations of the technology are the early rejection at the I-shader stage of the bounding boxes (AABBs) extracted by the RT-pipeline hardware unit, and the "transparent AABB" concept which allows transferring costly computing of the "ray-procedural object" intersection to a later AH-shader stage. The paper also describes a number of modifications that reduce the amount of such calculations. The proposed technology was implemented in a software complex in C++, GLSL and using the Vulkan API. The performance of the developed solution was studied under various ray tracing conditions on the task of modeling the surface of a detailed Puget Sound height field. The obtained results confirmed efficiency of the developed technology and the possibility of its application in virtual environment systems, simulators, scientific visualization, etc. [ABSTRACT FROM AUTHOR]

This paper considers the problem of constructing compartmental models of dynamic systems by using a software package for symbolic calculation written in Julia. The software package is aimed at unifying the formalized construction of compartmental models, taking into account the meaningful description of possible interactions among compartments and the influence of various factors on the evolution of systems. An approach to the development of the instrumental and methodological basis for modeling the dynamic systems the behavior of which can be described by one-step processes is developed. The proposed software package enables the symbolic representation of the differential equations of the model in both stochastic and deterministic cases. It is implemented in Julia and uses the Julia Symbolics computer algebra library. A comparison between the Julia Symbolics tools and some other computer algebra systems is carried out. The application of the developed software package to a compartmental model is considered. The results can be used to solve problems of constructing and studying dynamic models in natural sciences that are represented by one-step processes. [ABSTRACT FROM AUTHOR]

The process of developing C programs is quite often prone to errors associated with the use of pointer arithmetic and operations on memory addresses. Hence, the need for various automated program verification tools arises. One of the techniques frequently employed by these tools is invocation of suitable decision procedures implemented within existing SMT solvers. However, both the SMT standard and the majority of existing SMT solvers lack relevant logics (combinations of logical theories) for the direct and precise modeling of the semantics of pointer operations in C. A possible way to support these logics is to implement them in an SMT solver. However, this approach can be time-consuming (as it requires modifying the source code of the solver), inflexible (because introducing any changes to the signature or semantics of the theory can be unreasonably hard), and limited (every solver has to be supported individually). Another way is to design and implement custom quantifier instantiation strategies. These strategies can then be used to translate formulas in selected theory combinations into formulas in well-supported decidable logics, e.g., QF_UFLIA. In this paper, we present an instantiation procedure for translating formulas in the theory of bounded pointer arithmetic into the QF_UFLIA logic. We formally prove the soundness and completeness of our instantiation procedure in Isabelle/HOL. The paper also presents an informal description of this proof for the proposed procedure. The theory of bounded pointer arithmetic itself is formulated based on known errors associated with the use of pointer arithmetic operations in C, as well as based on the semantics of these operations specified in the C standard. Similar procedure can also be defined for a practically relevant fragment of the theory of bit vectors (monotone propositional combinations of equalities between bitwise expressions). Our approach is sufficient to derive efficient decision procedures, implemented as Isabelle/HOL proof methods, for several decidable logical theories used in C program verification by relying on the existing capabilities of well-known SMT solvers (e.g., Z3), as well as on the proof reconstruction capabilities of the Isabelle/HOL proof assistant. [ABSTRACT FROM AUTHOR]

DevOps is a philosophy and framework that allows software development and operations teams to work in a coordinated manner, with the purpose of developing and releasing software quickly and cheaply. However, the effectiveness and benefits of DevOps depend on several factors, as reported in the literature. In particular, several studies have been published on software test automation, which is a cornerstone for the continuous integration phase in DevOps, which needs to be identified and classified. This study consolidates and classifies the existing literature on automated tests in the DevOps context. For the study, a systematic mapping study was performed to identify and classify papers on automated testing in DevOps based on 8 research questions. In the query of 6 relevant databases, 3,312 were obtained; and then, after the selection process, 299 papers were selected as primary studies. Researchers maintain a continuing and growing interest in software testing in the DevOps context. Most of the research (71.2%) is carried out in the industry and is done on web applications and SOA. The most reported types of tests are unit and integration tests. [ABSTRACT FROM AUTHOR]

Brain Computer Interfaces- BCI allow users to communicate with the software system through cognitive functions measurable by brain signals, identified as Electroencephalography-EEG. User tests have been the most used method for the evaluation of BCI software applications. In user tests, the data collected comes from the opinions of users through questionnaires, these tests require a lot of time, since they include not only performing interaction task and the application of the questionnaires, but also include placing and calibrating the EEG device. All this makes the evaluation process a very heavy task for the participants and can mean that the data collected is not entirely reliable. That is why we are interested in including EEG signals in the usability evaluation process of applications with BCI. Therefore, we present in this paper the result of the systematic mapping of the literature in order to identify the relevant works in the area and future lines of research. [ABSTRACT FROM AUTHOR]

This paper investigates a simple case of the state-agent-environment model of artificial intelligence theory. The general framework of AI in this part provides search and planning and is based on the development of modelling mathematical formalisms with a consequent validation-check, and pathfinding stages. The application problem and the use case considered in this paper belongs to the domain of personalized medicine. The problem is known as the dynamic treatment regime (DTR), and we demonstrate that in addition to traditional AI techniques for such problems, a simpler graph theoretical development can be incorporated that solves the validation and pathfinding problems with less efforts and complexities. The results obtained are achieved by using graph connectivity checking algorithms, algorithms of pathfinding in rooted trees, and checking additional graph components to be a one dicycle cactus graph; and provide a means of consecutive restructuring the whole graph for the connectivity property that preserves the validated DTR policy. [ABSTRACT FROM AUTHOR]

The paper presents a study of robot interaction algorithms. The study of algorithms that control the behavior of robots is relevant due to the development of robotic means and their wide application in various fields: in manufacturing, medicine, military. The paper considers the application of nanorobot swarms in medicine. The study is performed using simulation methods. The simulation system NetLogo is used as a toolkit. The Netlogo simulation system is agent-based system. In the first part of the article, experiments using reactive agents are performed. Next, we consider intelligent agents that can make decisions related to the optimization of the algorithms by which they act. A series of experiments were carried out with intelligent agents and the values of parameters that affect the time of destruction of "bad" cells were determined. [ABSTRACT FROM AUTHOR]

The given paper discusses an original method of the evaluation of outcomes of adaptive testing in the case of the strategy of the multilevel testing. The multiplicity/set of the outcomes of testing consists of atypical different-dimensional elements. The given paper defines the criteria of their comparison, describes the principles of ordering of the given multiplicity and draws the getting of a final score. The paper presented considers the ordering method of outcome set for multi-stage testing (MST) of 1-3-3 model. The ordering method of outcome set is used for the estimation of results of computerized adaptive testing (CAT). This method is not tied to a specific testing procedure. Acknowledgment of this is its usage for the 1-3-3 model, which is described in the paper. To sort the set of testing outcomes the function-criteria described in the initial article are used here and a comparative analysis of obtained results is performed. The criterion of ordering of the outcomes of testing may not be the only option. The given paper illustrates this fact through a comparative discussion of two samples. An original procedure of testing is used for the presentation of the essence of the method. The given procedure is aimed to be illustrative, because a described method of assessment can be used for similar strategies. The ordered outcome set is estimated by a hundred-point system according to the normal distribution. Applied results of our scientific research is developed as "Adaptester" portal and available on the following address: https://adaptester.com. [ABSTRACT FROM AUTHOR]

Modern knowledge sharing platforms, such as Twitch, have gained significant popularity among developers. Twitch allows streamers (programmers) to broadcast real-time programming tasks across various domains. Viewers engage with streamers through live-chat messages, posting comments to other viewers or asking questions. However, the majority of comments are unhelpful, including spam and unrelated discussions. Streamers are faced with the challenge of identifying useful comments, either by reading the entire chat log, which diverts their attention from coding, or by periodically skimming through, risking the chance of missing important comments. Objective: Therefore, it is crucial to investigate and understand the content of viewer comments in live-streamed programming on Twitch. Method: In this paper, we present a manually labeled dataset of Twitch live-chat messages from programming streams. We conduct experiments to evaluate the accuracy of transformer-based models in automatically classifying these comments. Results: Our results illustrate that fine-tuning through training the BERT-base model with a specific preprocessing technique, @mention removal, can effectively classify Twitch live-chat messages with an F-score of 0.84. Conclusions: The outcomes of this work provide valuable insights for future research leveraging our labeled dataset, and the trained model can serve as a foundational approach for analyzing live stream platforms like Twitch. [ABSTRACT FROM AUTHOR]

Currently, digital technologies for modeling buildings and infrastructure are successfully used in international and national practice for the implementation of complex construction projects and large-scale programmes. At the same time, the transition to machine-readable standards, implemented in many countries to improve the quality of design documentation and automate its verification, faces serious methodological and technical challenges. First of all, these challenges are due to the complexity of digital models, as well as the variety of requirements formulated in natural languages and imposed on these models at the state, regional, departmental, and corporate levels. Attempts to create catalogs of requirements and software tools for their management and use generally have specific purposes and do not provide necessary completeness, normalization, consistency, interconnectedness, unambiguity, traceability, and validability of requirements description. In this regard, it seems reasonable to use formal methods for specification and verification of requirements that have proven themselves in system and software engineering. This paper provides a comparative analysis of software tools for automated verification of regulatory requirements in the construction domain. There is a growing interest in tools focused on international standards, such as Industry Foundation Classes (IFC) and Information Delivery Specification (IDS), that allow one to control the completeness of the object and attribute composition of models, as well as the clarification of acceptable domains of values values. However, the IDS standard is not formalized and does not enable the specification of requirements expressed in terms of arbitrary algebraic conditions. The EXPRESS object-oriented data modeling language, in which the IFC data schema is specified, seems promising for the formal specification and verification of requirements for digital models used in the construction industry. As a substantiation, it is shown that IDS specifications can be represented by logical expressions and EXPRESS functions, as well as that arbitrary algebraic conditions can be specified as EXPRESS declarative rules. To illustrate the proposed approach, we consider some examples of the formalization of requirements from national construction standards and sets of rules concerning the safety of buildings, structures, and processes. The possibility of harmonizing the proposed formal approach with the IDS standard by defining new facets for the representation of local, uniqueness, and global EXPRESS rules is also discussed. [ABSTRACT FROM AUTHOR]

Mathematical foundations and algorithms for recognizing bichromatic two-dimensional graphic codes, regardless of their type (QR codes, DataMatrix, GridMatrix, etc.) are presented. The stages of achieving the result include detecting the code, localizing it within an arbitrary quadrilateral, transforming the quadrilateral to a canonical square, constructing a grid of elements (modules) of the square code, and filling it with a sequence of bits. It is shown that perspective transformation formulas make it possible to transform localized quadrangular regions to canonical squares with an acceptable error level for further processing. A flat grid of square code elements is formed based on the search for extrema of the derivatives of the pixel intensity distribution of the square image along the axes x and y. The algorithm for filling grid cells (code modules) with a sequence of zeros and ones uses information about the average intensity of each such cell. At the end of the paper, the algorithms are tested on a variety of real images of two-dimensional codes, and the limitations of the proposed algorithms are examined. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of augmenting a set of histological images with adversarial examples to improve the robustness of neural network classifiers trained on the augmented set against adversarial attacks. In recent years, neural network methods have been developing rapidly, achieving impressive results. However, they are vulnerable to so-called adversarial attacks; i.e., they make incorrect predictions on input images with added carefully crafted imperceptible noise. Hence, the reliability of neural network methods remains an important area of research. In this paper, we compare different methods for training set augmentation to improve the robustness of neural histological image classifiers against adversarial attacks. For this purpose, we augment the training set with adversarial examples generated by several popular methods. [ABSTRACT FROM AUTHOR]

While modern rendering systems are efficient for modeling complex light paths in complex environments, the rendering of refractive caustics still takes a long time. Caustics are light patterns that occur when light is refracted and reflected from a surface. Due to an irregular density distribution of these specular events, rendering algorithms mainly rely on direct sampling of the bidirectional dispersion distribution function on these surfaces to plot trajectories. This requires a lot of calculations. Photonic maps are also used. However, there are difficulties that limit the applicability of caustic maps. Since each photon in the photon buffer must be processed, one has to choose between a strongly underestimated caustic sampling and a large decrease in speed in order to use a sufficient number of photons for caustics in order to obtain high-quality images. Complex specular interactions cause oversampling in bright focal areas, while other areas of the caustic map remain undersampled and noisy. At the same time, speed takes precedence over realism in most interactive applications. However, the desire to improve the quality of graphics prompted the development of various fast approximations for realistic lighting. This paper presents a combined method for rendering refraction of light and caustics using backward integration for illumination and direct integration for viewing rays. An approach for simultaneous propagation of light and for tracking rays in a volume is used; therefore, it does not require storing data of an intermediate volume of illumination. In the implementation of this method, the distance between the light planes is set to one voxel, which provides at least one sample per voxel for all orientations. The method does not use preliminary calculations, and all rendering parameters can be changed interactively. As a result, using the proposed method, it is possible to create plausible approximations of complex phenomena, such as refractions and caustics. The effect of refraction on the shadow is shown. Complex light patterns occurring due to the curved geometry of objects are demonstrated. The visualization results show the importance of refraction for the appearance of transparent objects, e.g., the effect distortions caused by refraction in the medium and refraction on the interfaces between media. The difference in refractive indices between different media causes a complex interaction between light and shadow areas. It is shown how refraction and caustics improve rendering of functionally defined objects by providing additional information about their shape and location. [ABSTRACT FROM AUTHOR]

This paper presents an extension for the Practice Library of the Essence language in the form of a practice for working with antipatterns. To represent antipatterns in a system, the Antipattern subalpha, its states, and checkpoints are proposed. To record data about an antipattern, the Antipattern Report work product and its levels of detail with checkpoints are proposed. To analyze the architecture of a system, the Inspect Architecture activity is proposed. The Fix Architecture activity represents actions for fixing architecture flaws. Code analysis is represented as the Review the Code activity, while the correction of deficiencies found during the analysis is represented as the Refactor the Code activity. The effect of the Antipattern subalpha on the state of the Software System alpha is analyzed. Some recommendations concerning the proposed activities are provided. [ABSTRACT FROM AUTHOR]

This paper presents results of development of a numerical model of Lagrangian particle transport, as well as results of application of parallel computation methods to improve the efficiency of the software implementation of this model. The model is a software package that allows the transport and deposition of aerosol particles to be calculated taking into account properties of particles and the input data that describe atmospheric conditions and underlying surface geometry. The dynamic core, physical parameterizations, numerical implementation, and algorithm of the model are described. Results of successful verification of the model on analytical solutions are presented. Initially, the model was used for less computationally intensive problems. In this paper, given the need to use the model in more computationally intensive problems, we optimize the sequential software implementation of the model, as well as develop its software implementations that use parallel computing technologies (OpenMP, MPI, and CUDA). The results of testing different implementations of the model show that the optimization of the most computationally complex blocks in its sequential version can reduce the execution time by 27%. At the same time, the use of parallel computing technologies allows us to achieve acceleration by several orders of magnitude. The use of OpenMP in the dynamic block of the model provides almost 4-fold acceleration of this block; the use of MPI, almost 8-fold acceleration; and the use of CUDA, almost 16-fold acceleration (all other conditions being equal). We also give some recommendations on the choice of a parallel computing technology depending on the properties of a computing system. [ABSTRACT FROM AUTHOR]

When a person suffers a stroke, they require rehabilitation to recover from the consequences caused by this event. In order to carry out the rehabilitation, a multidisciplinary team of specialists intervenes, providing care from diverse areas such as neurology, nutrition, psychology, and physiotherapy. In the rehabilitation process, physicians interact with medical computing software and devices. The interactions represent medical activities that follow rehabilitation. However, there is no clear conception of how specialists coordinate to carry out medical activities. There are no specific communication channels that allow multidisciplinary collaboration for complete rehabilitation. This paper presents a systematic review of the state of the art that addresses this problem. On the other hand, a collaborative software architecture is proposed to support this area, which allows the monitoring medical activities from human-computer multimodal interactions. The architecture is composed of 3 layers: (1) to perceive the interactions and to monitor the activities, (2) to control the multidisciplinary access and share the information, and (3) to analyze and evaluate the execution of the multidisciplinary activities. Evaluating how the activities are carried out will help the physicians make decisions regarding the execution of the treatment plan. Therefore, we propose an activities representation diagram that facilitates this evaluation. Finally, we developed a prototype with a user-centered design that perceives human-computer interactions supported by the architecture. [ABSTRACT FROM AUTHOR]

This paper shows quantitative research regarding knowledge, soft and hard skills, and experience acquired by students hired by a University Software Development Company (USDC). Additionally, suggestions regarding how to set up a USDC in an academic environment, facing real customers, are shown. There have been good and bad experiences, both will be presented in this paper. Furthermore, students' perceptions will be discussed. To identify students' perceptions a questionnaire (survey) was applied. Its reliability was calculated through Cronbach's alpha coefficient (α = 89). Additionally, the Pearson correlation coefficient was calculated (r) in order to identify questions that should be deleted to increase the questionnaire's reliability. Outcomes could be useful when a software engineering faculty wishes to set up a USDC. [ABSTRACT FROM AUTHOR]

This paper describes a static analysis tool for finding defects, analyzing metrics and relations for programs written in the Kotlin language. The approach is implemented in the Svace static analyzer developed at the Ivannikov Institute for System Programming of the Russian Academy of Sciences. The paper focuses on the problems we faced during the implementation, the approaches we used to solve them, and the experimental results for the tool we built. The tool not only supports Kotlin but is also capable of analyzing mixed projects that use both Java and Kotlin. We hope that this paper will be useful to static analysis developers and language designers. [ABSTRACT FROM AUTHOR]

This paper focuses on solving a subclass of stochastic nonconvex-nonconcave black box optimization problems with a saddle point that satisfy the Polyak–Łojasiewicz (PL) condition. To solve this problem, we provide the first (to our best knowledge) gradient-free algorithm. The proposed approach is based on applying a gradient approximation (kernel approximation) to an oracle-biased stochastic gradient descent algorithm. We present theoretical estimates that guarantee its global linear rate of convergence to the desired accuracy. The theoretical results are checked on a model example by comparison with an algorithm using Gaussian approximation. [ABSTRACT FROM AUTHOR]

The second smallest eigenvalue of the Laplacian is known as the algebraic connectivity of a graph. It shows degree of graph connectivity. However, this metric does not take into account possible changes in the graph. The removal of even one node or edge can make it disconnected. This work is devoted to the development of a metric that should describe robustness of a graph to such changes. All proposed metrics are based on the algebraic connectivity. In addition, we generalize some well-known optimization methods for our robust modifications of the algebraic connectivity. The paper also reports results of some numerical experiments demonstrating the efficiency of the proposed approaches. [ABSTRACT FROM AUTHOR]

This paper is devoted to some adaptive methods for variational inequalities with relatively smooth and relatively strongly monotone operators. Based on the recently proposed proximal version of the extragradient method for this class of problems, we study in detail the method with adaptively selected parameter values. The rate of convergence of this method is estimated. The result is generalized to the class of variational inequalities with relatively strongly monotone δ-generalized smooth operators. For the ridge regression problem and variational inequality associated with box-simplex games, numerical experiments are carried out to demonstrate the effectiveness of the proposed technique for adaptive parameter selection during the execution of the algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a variant of the Frank–Wolfe method for convex optimization problems with the adaptive selection of the step parameter corresponding to information about the smoothness of the objective function (the Lipschitz constant of the gradient). Theoretical estimates of the quality of the approximate solution provided by the method using adaptively selected parameters Lk are presented. For a class of problems on a convex feasible set with a convex objective function, the guaranteed convergence rate of the proposed method is sublinear. A special subclass of these problems (an objective function with the gradient dominance condition) is considered and the convergence rate of the method using adaptively selected parameters Lk is estimated. An important feature of the result obtained is the elaboration of the case where it is possible to guarantee, after the completion of the iteration, at least double reduction in the residual of the function. At the same time, the use of adaptively selected parameters in theoretical estimates makes the method applicable to both smooth and non-smooth problems, provided that the iteration termination criterion is met. For smooth problems, it can be proved that the theoretical estimates of the method are reliably optimal up to multiplication by a constant factor. Computational experiments are carried out and a comparison with two other algorithms is made to demonstrate the efficiency of the algorithm on a number of both smooth and non-smooth problems. [ABSTRACT FROM AUTHOR]

In this paper, we consider a generalization of the decentralized Frank–Wolfe algorithm to time-varying networks, investigate the convergence properties of the algorithm, and carry out the corresponding numerical experiments. The time-varying network is modeled as a deterministic or stochastic sequence of graphs. [ABSTRACT FROM AUTHOR]

Grammatical error correction is one of the core natural language processing tasks. Presently, the open-source state-of-the-art sequence tagging for English is the GECToR model. For Russian, this problem does not have equally effective solutions due to the lack of annotated datasets, which motivated the current research. In this paper, we describe the process of creating a synthetic dataset and training the model on it. The GECToR architecture is adapted for the Russian language, and it is called RuGECToR. This architecture is chosen because, unlike the sequence-to-sequence approach, it is easy to interpret and does not require a lot of training data. The aim is to train the model in such a way that it generalizes the morphological properties of the language rather than adapts to a specific training sample. The presented model achieves the quality of 82.5 in the metric on synthetic data and 22.2 on the RULEC dataset, which was not used at the training stage. [ABSTRACT FROM AUTHOR]

In this paper, the authors present a technique for developing a secure messaging service called "CryptoMess" which utilizes the Commutative Supersingular Isogeny Diffie-Hellman (CSIDH) algorithm for secure key exchange and the Advanced Encryption Standard (AES) to protect message content in communication. In addition, the authors have incorporated the Falcon post-quantum digital signature technology to ensure the integrity and authenticity of communications between the sender and the recipient. The novel post-quantum cryptographic algorithms utilized by the authors are still under consideration in the competition to select cryptosystems for use in quantum computing systems organized by the NIST Standards Institute. As a result, the messaging program "CryptoMess" is able to exchange messages between users, providing safety, security, integrity, and authenticity. The authors have included modern post-quantum cryptography techniques, such as the Falcon digital signature system, to guarantee that the product operates safely. The program has a transmitting rate of approximately 209–261 ms and a receiving rate of approximately 168–206 ms. The message signing time is about 260 ms, and the message verification speed is approximately 185 ms. Key generation time is about 741 ms, key encapsulation time is about 1.454 ms, and key decapsulation time is about 1.921 ms. The source code of the "CryptoMess" communications program has been analyzed and tested by the authors using the Fortify Static Code Analyzer tool to ensure that the product has been created safely and securely. [ABSTRACT FROM AUTHOR]

This paper presents a comparative efficiency analysis of hashing algorithms from a perspective of their use in systems based on the zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK). Hash functions sha256, sha3, poseidon, mimc, and blake2, most commonly used in modern distributed ledgers, are considered. For parameter measurement experiments, an infrastructure using the ZoKrates toolbox is developed. Based on experimental data, the limits of practical applicability of the algorithms to the problem of proving knowledge of a hash preimage with zk-SNARK circuits in distributed ledgers are determined, and related efficiency problems are considered. [ABSTRACT FROM AUTHOR]

This paper explores the possibility of using dual representation of geometry to speed up ray tracing and ensure robustness of light propagation simulation in complex optical systems with freeform surfaces defined by high-degree polynomials (up to order 34) or Jacobi polynomials. Traditional methods for representing this geometry both as a triangular mesh and as an analytical expression are analyzed. The analysis demonstrates the disadvantages of the traditional approaches due to the insufficient accuracy of calculating coordinates of the point at which the ray intersects the triangular mesh, as well as the non-robustness of the conventional procedures for finding the point of intersection between the tangent ray and the analytical surface. Thus, it is proposed to use a dual representation of geometry as a rough approximation of the surface by a triangular mesh, which is subsequently used as an initial approximation to find the point at which the ray intersects the surface defined by an analytical expression. This approach significantly speeds up convergence of the analytical methods and improves robustness of their solutions. The use of the Intel® Embree library to quickly find the point of intersection between the ray and the rough triangular mesh, as well as a vector model to refine the coordinates of the point of intersection between the ray and the analytically represented geometry, allows us to develop and implement a ray tracing algorithm for an optical system that has surfaces with dual representation of geometry. Experiments carried out using the developed algorithm show a significant speedup of ray tracing while preserving computational accuracy and high robustness of the results. The results are demonstrated by evaluating the point spread function and glare for two lenses with freeform surfaces defined by Jacobi polynomials. In addition, for these two lenses, an image formed by an RGB-D object that simulates a real scene is calculated. [ABSTRACT FROM AUTHOR]

In the modern world, digital image processing requires increasing the speed of the processing methods and algorithms used. One way to improve performance is to transform spatial filters into filters with a recursively separable form of implementation. The recursion property implies the use of previous output values of a function to form the current sample. The property of separability is understood as division into processing by column and row of a matrix of digital image values. The transformation of spatial filters consists of changing the aperture of the masks into a non-orthogonal (non-equilateral) form, which reduces the number of computational operations and speeds up the processing process, while maintaining its efficiency. The paper presents a description of the non-equilateral apertures of the previously developed Laplacian digital filters "truncated pyramid" and "double pyramid." For non-equilateral apertures, results were obtained for the first time on their use for television measuring systems. From which it can be seen that a "truncated pyramid" Laplacian filter with non-equilateral processing apertures is recommended for use in TIS, since it increases the efficiency of measuring the range to objects of interest while reducing processing time. Based on the results of processing with modified filters, sets of processed images were obtained for each of the 10 original images. For each set of processed images, measurements of the peak signal-to-noise ratio, standard deviation and selection of the optimal central coefficient of the filter mask were carried out, for subsequent assessment of the effectiveness of processing with modified filters. The assessment of the influence of recursively separable Laplacian filters "truncated pyramid" and "double pyramid" with non-equilateral aperture masks on the accuracy of television measurement systems consisted of considering their influence on measuring the distance (from the camera) to the object of interest in the image, when - control of processing time. Based on the evaluation results, we can conclude that by using pre-processing of images with modified digital filters, the accuracy of measuring the distance from the camera to the measurement object is improved, while reducing processing time. [ABSTRACT FROM AUTHOR]

This paper presents an approach to 3D model reconstruction from point cloud data using modern neural network architectures. The method is based on PointNet++ and Transformer. PointNet++ plays a key role, providing efficient feature extraction and encoding of complex geometries in 3D scenes. This is achieved by recursively applying PointNet++ to nested partitions of the input point set in a metric space. Convex decomposition, which is an important step in the proposed approach, transforms complex 3D objects into sets of simpler convex shapes. This facilitates data processing and makes the reconstruction process more manageable. Then, Transformer trains the model on the extracted features, which enables the generation of high-quality reconstructions. It should be noted that Transformer is used only to determine positions of the walls and detect object boundaries. This combination of technologies allows us to achieve high accuracy of 3D model reconstruction. The main idea of the method is to segment the point cloud into small fragments, which are then reconstructed as polygon meshes. To restore missing points in point cloud data, a method based on the L1-median algorithm and local features of the point cloud is used. This approach can adapt to different geometric structures and correct topological connectivity errors. The proposed method is compared with several modern approaches, demonstrating its potential in various fields, including architecture, engineering, digitalization of cultural heritage, as well as augmented and mixed reality systems. This confirms its wide applicability and great perspectives for further development. [ABSTRACT FROM AUTHOR]

The set of polynomial mappings of n-dimensional complex space into itself the Jacobian matrix of which has a constant nonzero determinant is known to be very vast in any dimension that exceeds one. The well-known Jacobian conjecture states that any such mapping is polynomially invertible. Even though the computation of the determinant of the Jacobian matrix is very well supported in modern computer algebra systems, the algorithmic inversion of a polynomial mapping is still a problem of considerable computational complexity. In this paper, we present a Mathematica package JC that can be used for construction and inversion of polynomial mappings and more general analytic mappings with the unit determinant of the Jacobian matrix. The package includes functions that allow one to algorithmically construct these mappings for a given dimension of the space of variables and a given degree of mapping components. The package, together with a library of datasets for testing it and results of computational experiments, is available for free public use at https://www.researchgate.net/publication/358409332_JC_Package_and_Datasets. [ABSTRACT FROM AUTHOR]

It is intuitively clear that search for scientific publications often has many characteristics of exploratory search. The purpose of this paper is to formalize this intuitive understanding, explore which scientific search tasks can be classified as research search ones, what general approaches to the research search problem exist, and how they are implemented in specialized search engines for scientists. We overview the existing works that address the information-seeking behavior of scientists and a special variant of search called exploratory search. There are several types of search behavior typical for scientists; we show that most of them are exploratory ones. Exploratory search differs from information retrieval and requires special support from the search systems. We analyze seventeen search systems for academicians (from Google Scholar, Scopus, and Web of Science to ResearchGate) from the perspective of exploratory search support. We find that most of them do not go far beyond simple information retrieval, and there is room for further improvements, especially in collaborative search support. [ABSTRACT FROM AUTHOR]

Automation of C program verification is an important problem in modern software development. To solve this problem, the solution of the following problems must be automated: loop invariants, proof of verification conditions, and localization of errors in the case of invalid verification conditions. To this end, the C-lightVer system is under development in the Ershov Institute of Informatics Systems of the Siberian Branch of the Russian Academy of Sciences. This system uses an integrated approach to the automated deductive verification of C programs. This approach includes a symbolic method of verification of definite iterations for eliminating loop invariants, strategies for proving verification conditions, and a method for error localization. The symbolic method of verification of definite iterations is based on replacing the action of certain loops by the application of a special recursive function rep. The error localization method is based on matching the verification conditions to the source code and on generation of a report about the correspondence between the verification conditions and program fragments. Thus, the problem of automation of verification of C programs containing nested loops naturally arises. The application of the symbolic method of verification of definite iterations for such programs leads to a composition of the functions rep for outer and inner loops. A novel result obtained in this paper is a strategy of automation of proof of verification conditions for such programs. This strategy is based on induction on the index of iteration in the outer loop. To prove the induction step, another result obtained in this paper is used. This is a strategy for programs the specification of which contains functions with the concatenation property. The paper also describes strategies of error localization and modifications of the error localization method for the case of nested loops. These strategies are also used for verifying the loop properties that may indicate the presence of errors. As an example of applying the results obtained in this paper, automatic verification of insertion sort without loop invariants is considered. [ABSTRACT FROM AUTHOR]