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Two approaches to determining similarity of two digraphs
Journal of Computer and Systems Sciences International. 2012. Vol. 51. No. 5. P. 695–714.
Kokhov V. A.
An approach to solving the problem of determining similarity with application of a maximal common fragment of two graphs is considered. Its two main disadvantages are specified. Two new approaches to solving the problem of determining similarity of digraphs are proposedamp;: a generalized substructural-metric approach and an approach using a stratified system of matrix models of the digraph complexity. New features for investigating similarity of digraphs are formulated. The original problem of calculating similarity of layout of fragments in the digraph is formalized with account of quantitative and qualitative features of fragments of the digraph. A methodology, involving two systems of methods for solving the problem, is developed. The first system of methods takes into account the precise layout of fragments in the digraph, while the second one deals with the approximate layout of fragments. A new class of problems is distinguished, which consists in calculating similarity of digraphs with account of similarity of the layout of fragments of the specified type. An example of solving the problem of finding semantic networks that are most similar to a network-template is presented.
Kertesz-Farkas A., Acquaye F. L., Journal of Proteome Research 2026 Vol. 25 P. 3764–3768
Ultimately, most tandem mass spectrometry (MS/MS) proteomics experiments aim to not just detect but also quantify the proteins in a given complex sample. Here, we describe an extension to the Crux MS/MS analysis toolkit to enable label-free quantification of peptides. We demonstrate that Crux’s new quantification command, which is modeled after the algorithms implemented in ...
Added: September 23, 2026
Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Risk Analysis 2026 Vol. 46 No. 4 P. 1–26
Heated tobacco products (HTPs) are marketed as alternatives to conventional cigarettes with a potential reduced risk profile. Yet, their actual impact on cancer and noncancer disease risk remains uncertain and requires rigorous quantitative assessment. In this study, we develop a unified and transparent computational framework for toxicological risk assessment of HTPs, integrating chemical emissions data ...
Added: September 22, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 855–862
Tasks related to the automation of medical data processing are becoming more urgent. Particular attention is paid to systems for monitoring and analyzing human physiological parameters. Such systems often use specialized sensors to capture biomedical images, such as infrared cameras. This article describes our study of the problem of segmenting the eye pupil and iris ...
Added: September 21, 2026
Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854
Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Optical Memory and Neural Networks (Information Optics) 2024 Vol. 33 P. 424–434
This study explores the development of classifiers for microbial images, specifically focusing on streptococci captured via microscopy of live samples. Our approach uses AutoML-based techniques and automates the creation and analysis of feature spaces to produce optimal descriptors for classifying these microscopic images. This technique leverages interpretable taxonomic features based on the external geometric attributes ...
Added: September 21, 2026
Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1053–1060
This paper presents a novel approach to classification in biomedical imaging, specifically targeting polyp recognition in video endoscopy snapshots. Our method leverages specialized image descriptors to enhance the accuracy and robustness of polyp recognition. By employing these specialized descriptors, we address the challenges inherent in analyzing biomedical images from open datasets. Our approach not only ...
Added: September 21, 2026
Самарин А. В., Торопов А. Г., Савельев А. Г. et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1044–1052
This paper presents a study aimed at improving the detection quality of small-sized microorganisms under challenging microscopic conditions through the application of a lightweight combined image preprocessing model. We focused on the task of detecting diplococci in images obtained through dynamic sample microscopy. The proposed approach employs predefined filters for image preprocessing, combined with the ...
Added: September 21, 2026
Singapore: Springer Singapore, 2025.
Added: September 21, 2026
Tomat A., Sergei O. Kuznetsov, International Journal of Approximate Reasoning 2026 Vol. 197 Article 109754
Interval Pattern Structures (IPS) provide a natural way to represent local, human-readable explanations for predictions on numerical data through vectors of intervals interpreted as axis-parallel hyper-rectangles. In this paper, we develop and evaluate an IPS-based k-nearest neighbors classifier, IPS-KNN, that explains each prediction through a single local interval description rather than through the aggregation of ...
Added: September 21, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., / Series arXiv "math". 2025. No. 2511.20141.
This paper presents a novel approach to neural network compression that addresses redundancy at both the filter and architectural levels through a unified framework grounded in information flow analysis. Building on the concept of tensor flow divergence, which quantifies how information is transformed across network layers, we develop a two-stage optimization process. The first stage ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2025 Vol. 35 No. 2 P. 169–178
This study explores the incorporation of specialized self-attention mechanisms into deep learning architectures, with a particular emphasis on segmenting human iris and pupil regions in infrared images. In this work, we present some modified versions of nonlocal blocks designed to enhance self-attentive properties while addressing the distinct characteristics of infrared imaging data. By applying these customized ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 10 Article 359
Timely identification and accurate delineation of ultra-early ischemic stroke lesions in non-contrast computed tomography (CT) scans of the human brain are of paramount importance for prompt medical intervention and improved patient outcomes. In this study, we propose a deep learning-driven methodology specifically designed for segmenting ultra-early ischemic regions, with a particular emphasis on both the ...
Added: September 21, 2026
Springer, Cham, 2025.
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 6 P. 1–20
This study presents a unified low-parameter approach to multi-class classification of microorganisms (micrococci, diplococci, streptococci, and bacilli) based on automated machine learning. The method is designed to produce interpretable taxonomic descriptors through analysis of the external geometric characteristics of microorganisms, including cell shape, colony organization, and dynamic behavior in unfixed microscopic scenes. A key advantage ...
Added: September 21, 2026
Springer, 2026.
Two volumes of the SPECOM 2026 proceedings contain a collection of submitted papers presented at SPECOM 2026, which were thoroughly reviewed by members of the Program Committee and additional reviewers consisting of almost 80 experts in the conference topic areas. In total, 65 regular full papers out of 99 submissions made via the EasyChair electronic ...
Added: September 20, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2026 Vol. 36 No. 2 P. 323–334
In this paper, an improved approach for automatic wildlife detection in natural environments based on the integration of a neural network architecture with a two-stream attention mechanism and a novel preclassification step based on infrared data has been presented. The proposed method addresses one of the key challenges in environmental monitoring: the need for scalable ...
Added: September 19, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., Proceedings of the ACM on Management of Data, USA 2026 Vol. 4 No. 1 P. 1–28
Modern knowledge and large volumes of data are increasingly encoded within neural networks, making the task of simplifying their structures and reducing the number of parameters especially relevant, both to improve efficiency and to facilitate deployment in resource-constrained environments. This paper presents a novel approach to neural network compression that addresses redundancy at both the ...
Added: September 19, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2025 Vol. 35 No. 2 P. 148–158
This paper describes our research on creating classifiers for microbial images (micrococci microscopy images) obtained from pictures of unfixed microscopic scenes. In our work, we propose an AutoML approach based on the automatic generation and analysis of the feature space for constructing the most optimal descriptors of microorganism images for subsequent classification. This makes it ...
Added: September 19, 2026
Kulev Y., Maksaev A., Promyslov V., Linear Algebra and its Applications 2026 Vol. 730 P. 51–72
The notion of λ-th upper scrambling index was introduced by Huang and Liu in 2010, as a generalization of a notion considered by Akelbek and Kirkland in 2009. For a primitive digraph D, it is defined as the smallest positive integer k such that for every λ vertices of D there exist directed paths of lengths k from these vertices to a common vertex. This ...
Added: August 7, 2026
М.: Институт русского языка им. В.В. Виноградова РАН, 2026.
Сборник тезисов Пятнадцатых Шмелёвских чтений (К 100-летию со дня рождения академика Дмитрия Николаевича Шмелева) Жизнь слова: Научное наследие академика Д. Н. Шмелева в контексте современности. Охватывает разные аспекты современной русистики: от исторической лексикологии до современных трансформаций прагматики и семантики слов. ...
Added: June 23, 2026
Калуга: ФБГОУ ВПО "Калужский государственный университет им. К.Э.Циолковского", 2025.
В настоящем сборнике представлены доклады ученых-лингвистов из разных стран (России, Беларуси, Молдовы, КНР) по итогам Международной научной конференции, посвященной памяти доктора филологических наук, профессора Ольги Павловны Ермаковой, «Проблемы семантики и прагматики языковых единиц разных уровней в эпоху больших языковых данных», которая проходила на базе Калужского госуниверситета 28 - 30 июня 2025 года и была посвящена ...
Added: April 3, 2026
Trofimova N., Pesina S., Vinogradova S. et al., Brazilian Journal of Education, Technology and Society - BRAJETS 2025 Vol. 17 No. 3 P. 126–136
n this article, we have proposed to differentiate textual and lexical metaphtonymy as different phenomena. We have considered the phenomenon of metaphtonymy at the level of text, a chain of words the length of a sentence, a phrase, and a separate meaning. We propose to reserve the term “metaphtonymy” for cases when we are talking ...
Added: February 22, 2026
Тамбов: Тамбовский государственный университет им. Г.Р. Державина, 2025.
"Cognitive Studies of Language" is a leading scientific field and periodical studying language as a cognitive mechanism, a tool for conceptualizing and categorizing the world, storing and processing information. It analyzes the relationship between language, consciousness, and mental processes, including conceptual analysis, frame semantics, and modeling, drawing on the work of Russian and international experts.
The ...
Added: February 22, 2026
Gladkova A., , in: Explorations in Applied Ethnolinguistics: Words, Cultures, and Global Perspectives.: Palgrave Macmillan, 2025. Ch. 8 P. 149–162.
This chapter is a reflective analysis of the author’s experience of translating The Story of God and People (henceforth: The Story) from Anna Wierzbicka’s book What Christians Believe: The Story of God and People in Minimal English from English into Russian (Wierzbicka, 2019; Vežbickaja, 2021). ...
Added: January 28, 2026