articles
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№ 1(115)
24 february 2025 year
Rubric: Researching of processes and systems The author: Perevaryukha A. |
Analysis of epidemic processes is one of the oldest tasks for the application of modeling methods in the field of studying the state of society. Despite the availability of many approaches to the development of epidemic models, experts were unable to timely obtain an acceptable forecast for the ongoing spread of coronavirus in the winter of 2024. With new waves, the updated virus has returned once again after victory over the infection was declared. The possibilities and problems of office structures based on modifications of SIR models for a modern epidemic stage of a virus that continues to mutate are determined. The global dynamics of infections changed the oscillation mode twice: after the peak in the spring of 2022 and in the winter of 2024. After the global Omicron wave, local epidemics acquired an asynchronous character based on the formation and attenuation of a series of waves. The frequency of occurrence of individual infection peaks varied significantly across regions already in 2020. In some countries, frequent short waves of large amplitude developed. We classified the scenarios according to the characteristic features of their nonlinear dynamics. We proposed a method for modeling the sharp development of spread of the virus based on equations with threshold regulation functions that describe variants of the formation of outbreaks of infections and situational damping functions that determine the form of oscillating attenuation for the number of infections. The fading trend after primary wave in the model is interrupted by a mass infection event, which induces an outbreak of infections and then a new regime of fluctuation attenuation follows. Our computational experiment simulates the development of an extreme peak after the stage of attenuation of waves of a local epidemic as a bifurcation scenario for the reactivation of waves of the SARS-CoV-2 coronavirus activity, which is due to effect of a crowded disease. Continue... |
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| All steganographic methods are focused on a specific container file format. Text documents with markup are the most difficult object for steganography methods. The article suggests a model for embedding structured text documents in control tags. The model uses the document tree structure and embeds into free leaf nodes. This approach adds hidden data that does not affect the display of the document. Two steganographic methods are implemented based on this model. The first method embeds hidden data into html document tags. The embedding method adds underplayed tags and style classes to free leaf nodes. The hidden data extraction method uses the embedding identifier. This role is played by the name of the new class. The name generation algorithm is based on the embedding key and hash function. The format of the identifiers matches the format of the source document names. This naming method allows the hidden message blocks to be randomly allocated to free leaf nodes. The second method embeds steganographic inserts into xml documents. Hidden data is added to the free leaf node attributes. The method requires two new attributes to execute. The optional structure describes both attributes. The format of this structure is indistinguishable from the structures present in the document. The embedding identifier is also based on the embedding key and the embedded block number. The data view uses an encryption algorithm with an additional key. Both methods use embedded data masking to counteract source code steganalysis. Steganalysis of such methods has exponential algorithmic complexity, so both methods are only applicable to large files. Continue... |
