?
Modeling Business Capabilities in Enterprise Architecture Practice: The Case of Business Capability Models
Information Systems Management. 2024. Vol. 41. No. 2. P. 201–223.
Kotusev S., Alwadain A.
Business capability modeling is a narrow domain of enterprise architecture modeling, which currently remains insufficiently explored. This study identifies nine general business capability modeling approaches and corresponding usage scenarios of business capability models most of which have not been systematically described or even mentioned in the existing literature. This study represents arguably the first intentional effort to explore the practical usage of business capability models in organizations for the purposes of aligning business and IT.
Qian X., Guan X., Zhang B. et al., Journal of Global Optimization 2026
Inverse quickest path problem on networks ...
Added: September 27, 2026
Switzerland: Springer Cham, 2026.
This volume gathers selected, peer-reviewed contributions presented at the 19th Conference of the International Federation of Classification Societies (IFCS 2026), held on 14–16 July 2026 in Milan, Italy. Reflecting the volume’s motto, Navigating Complexity – Statistical Methods, Data Analysis, and Machine Learning for Actionable Insights, the papers showcase modern methodologies and real-world applications designed to extract ...
Added: September 25, 2026
Kraevskiy A., Sokolovskiy E., Prokhorov A., Emerging Markets Review 2026 No. 74 P. 1–19
Financial markets of emerging economies are vulnerable to extreme and cascading information spillovers, surges, sudden stops and reversals. With this in mind, we develop a new online early warning system (EWS) to detect what is referred to as ‘concept drift’ in machine learning, as a ‘regime shift’ in economics and as a ‘change-point’ in statistics. ...
Added: September 25, 2026
Дубич Е. В., Schagin D., Славянский форум 2026 № 2 (52) С. 560–565
The paper compares HTTP/2 and HTTP/3 for static resource transfer under software-simulated network degradation. The experiment shows that HTTP/3 is not universally faster, but it is more stable as latency and packet loss increase. ...
Added: September 25, 2026
Joulitov A.K., Lomazova I.A., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4(2) P. 215–224
In process mining, DFG (Directly-Follows Graph) models are popular due to their simplicity and clarity. However, if a process is acyclic but contains concurrent events, standard algorithms for discovering DFG models can generate "fake" cycles that do not actually exist in the event log. These cycles hinder the analysis of information processes, significantly reducing the ...
Added: September 24, 2026
Добрина Д. Н., Nesterenko A., Прикладная дискретная математика. Приложение 2026 № 19 С. 151–159
Работа содержит результаты формального анализа криптографических механизмов, входящих в состав проекта методических рекомендаций «Защищенный универсальный протокол передачи данных и управления микросхемой интеллектуальной карты» (протокол SECUNDA). Получена формальная модель и перечень трудноразрешимых математических задач, трудоёмкостью решения которых можно оценить стойкость используемых криптографических механизмов. ...
Added: September 24, 2026
I.I. Sergeev, I.A. Lomazova, Modeling and Analysis of Information Systems 2026 Vol. 33 No. 3 P. 394–419
Object-centric process mining has emerged as a powerful paradigm for analyzing event data involving multiple interacting business objects. Existing discovery techniques often rely on object-centric Petri nets with fixed arc multiplicities, limiting their ability to represent parametric resource consumption and production patterns and to capture quantitative dependencies between interacting object types. In this paper, we ...
Added: September 24, 2026
Ivan Bulychev, Savchenko A., AI 2026 Vol. 7 No. 9 Article 380
Recent advances in large language model (LLM) agents have shown promise for autonomous decision-making in recommender systems. However, existing approaches suffer from two fundamental limitations: flat agent memories that conflate different information modalities and prohibitive computational costs that prevent scaling beyond a few hundred users. We propose Hybrid-GraphRAG, a recommender system that integrates hierarchical agent ...
Added: September 24, 2026
Snegirev A., Sychev S., Futures 2026 Vol. 183 P. 1–22
This study addresses the systemic identification and categorization of risks associated with AI development, arising from tensions between technological evolution and institutional, infrastructural, and economic contexts. Drawing on a constructionist methodology, we interpret technological risks as constitutive elements of expert communities' images of the future. Through in-depth interviews with 100 AI experts, proportionally representing corporate, ...
Added: September 23, 2026
Parshakov P., Paklina S., International Journal of Human-Computer Interaction 2026 P. 1–17
This study examines how emotional tone shapes user preference in human–large language model (LLM) interaction. Drawing on the Computers as Social Actors framework, we treat conversational AI as a social communicator whose affective cues influence user judgments. Using large-scale pairwise preference data from LMSYS Chatbot Arena, we model emotional tone through the Valence–Arousal–Dominance framework and ...
Added: September 23, 2026
Andrabi U., Wadood E., Ojha S. K. et al., IEEE Access 2026 Vol. 14 P. 103358–103375
The emergence of 5G networks, aimed at accommodating diverse service requirements such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC), has presented significant challenges in radio resource management and network slicing. In dynamic heterogeneous network systems, traditional heuristics and mathematical programming methods find it challenging to attain scalable multi-objective ...
Added: September 23, 2026
Paklina S., Parshakov P., Elena Rapoport, Scientometrics 2026 P. 1–26
Generative artificial intelligence has become a routine part of academic writing. While much of the debate has focused on questions of integrity and authorship, less attention has been paid to how AI-assisted writing may affect research evaluation itself. This paper asks a straightforward but important question: does the use of LLMs in academic writing change ...
Added: September 23, 2026
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
Kotusev S., Kurnia S., Dilnutt R., Information and Software Technology 2022 Vol. 147 No. 1 Article 106897
Context: Enterprise architecture (EA) is a description of an enterprise from an integrated business and IT perspective. EA is typically defined as a comprehensive blueprint of an organization covering its business, data, applications and technology domains and consisting of diverse EA artifacts. EA has numerous potential stakeholders and usage scenarios in organizations. However, the existing ...
Added: May 1, 2022
Kotusev S., Kurnia S., Dilnutt R., Aslib Journal of Information Management 2022 Vol. 74 No. 3 P. 432–457
Purpose – Information architecture (IA) is often understood as a comprehensive master plan for organizational data assets and is widely considered as an essential component of broader enterprise architecture (EA). However, the status and practical operationalization of IA still remain largely unclear. In order to clarify these questions, this paper investigates what instruments related to ...
Added: December 6, 2021
Kotusev S., Kurnia S., Dilnutt R., , in: Proceedings of the 41st International Conference on Information SystemsVol. 41.: Association for Information Systems, 2020. P. 1–17.
Added: December 17, 2020
van de Wetering R., Kurnia S., Kotusev S., Sustainability 2020 Vol. 12 No. 21 Article 8902
In recent years, the literature has emphasized theory building in the context of Enterprise Architecture (EA) research. Specifically, scholars tend to focus on EA-based capabilities that organize and deploy organization-specific resources to align strategic objectives with the technology’s particular use. Despite the growth in EA studies, substantial gaps remain in the literature. The most substantial ...
Added: December 17, 2020
Kotusev S., Pacific Asia Journal of the Association for Information Systems 2018 Vol. 10 No. 4 P. 1–36
Enterprise architecture (EA) is a description of an organization from an integrated business and IT perspective. Current literature conceptualizes EA as a comprehensive blueprint of an enterprise organized according to a logical framework and describing its current state, desired future state and migration roadmap. However, the current concept of EA originates from non-empirical sources, lacks ...
Added: October 18, 2019
Kotusev S., International Journal of Enterprise Information Systems 2017 Vol. 13 No. 2 P. 50–62
The current enterprise architecture (EA) theory originates from the Business Systems Planning (BSP) methodology initiated by IBM in the 1960s and describes EA as a comprehensive blueprint of an enterprise organized according to a certain framework and describing the current state, the desired future state and the roadmap for transition between them. However, in this ...
Added: October 18, 2019