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It has been a proven fact that the inclusion of more than one modality makes biometric recognition systems more robust and elevates its recognition accuracy. This paper aims to develop a strategic platform for the upcoming researchers in order to develop multimodal biometric recognition systems. The researchers in this fraternity would be able to design their own procedural strategy using the generalized workflow template depicted in this review. The selection of proper visually interpreted biometric identifiers and modalities, various fusion strategies, choice of performance metrics, formation of training and test sets from databases and the possible challenges in developing the workflow are purposefully portrayed in this article.

Ensuring trust in cryptographically secure algorithm implementations is a relevant task in modern programming. Because increased correctness requirements are imposed on such software systems, the proof of their correctness with respect to a certain formal specification is constructed via deductive verification. This article outlines the progress made towards the proof of correctness of the Streebog hash function implementation located in the Linux kernel with respect to the GOST R 34.11-2012 standard. The work began as part of the "Formal verification of a Streebog hash function implementation with the Astra Group" project during the 2025 Great Mathematical Workshop. As the result of our work we present a formalization of the GOST R 34.11-2012 algorithm in the Rocq proof assistant's Gallina language. This formalization can serve as a functional specification for any implementation of the Streebog hash function. We also present specifications for some of the basic functions present in the Streebog hash function implementation located in the Linux kernel and also methods of simplifying proofs of correctness of such functions by formulating lemmata that establish a correspondence between the data structures present in the implementation and the data structures outlined in the functional specification.

The article presents a comprehensive overview of modern near-Earth space geospatial monitoring systems aimed at providing protection from space debris and asteroid hazards. The review examines existing and promising technologies, including methods of surveillance, active threat removal, and the use of information systems. Special attention is paid to the role of artificial intelligence and automation in improving monitoring efficiency.