collaborators

7 papers

cs.NI2025

The Role of Fractal Dimension in Wireless Mesh Network Performance

Marat Zaidyn, Sayat Akhtanov, Dana Turlykozhayeva +4

Wireless mesh networks (WMNs) depend on the spatial distribution of nodes, which directly influences connectivity, routing efficiency, and overall network performance. Conventional…

astro-ph.IM2025

Luminis Stellarum et Machina: Applications of Machine Learning in Light Curve Analysis

Almat Akhmetali, Alisher Zhunuskanov, Aknur Sakan +4

The rapid advancement of observational capabilities in astronomy has led to an exponential growth in the volume of light curve (LC) data, creating both opportunities and challenges…

astro-ph.SR2025

Machine learning-based classification of variable stars using phase-folded light curves

Almat Akhmetali, Alisher Zhunuskanov, Timur Namazbayev +4

Classifying variable stars is crucial for advancing our understanding of stellar evolution and dynamics. As large-scale surveys generate increasing volumes of light curve data, the…

cs.NI2024

MEGA: Maximum-Entropy Genetic Algorithm for Router Nodes Placement in Wireless Mesh Networks

N. Ussipov, S. Akhtanov, D. Turlykozhayeva +7

Over the past decade, Wireless Mesh Networks (WMNs) have seen significant advancements due to their simple deployment, cost-effectiveness, ease of implementation and reliable servi…

cs.NI2024

Single Gateway Placement in Wireless Mesh Networks

D. A. Turlykozhayeva, W. Waldemar, A. B. Akhmetali +3

Wireless Mesh Networks (WMNs) are crucial for various sectors due to their adaptability and scalability, providing robust connectivity where traditional wired networks are impracti…

eess.SP2024

Automatic modulation classification for MIMO system based on the mutual information feature extraction

N. Ussipov, S. Akhtanov, Z. Zhanabaev +6

Automatic Modulation Classification (AMC) is an essential technology that is widely applied into various communications scenarios. In recent years, many Machine Learning and Deep-L…