The concept of sustanaible development in the globalization of the world economy by Оksana Urban, Мykola Dziamulych, Natalia Chyzh

“…That is why the work is focused on finding opportunities to minimize the negative impact of global problems on socio-economic network processes. And therefore, the decisive step to the further spread of the concept of sustainable development is regional implementation in accordance with existing local problems. …”
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Prediction of Network Threats and Attacks by Mathematical Simulation by Daniil Doroshenko

“…The study showed that mathematical models do not allow analyzing complex network processes, predicting the emergence of new threats and identifying vulnerabilities in networks. …”
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Rediscovery of Social Reality of the City and the Village: Methodological Novations of the Study of Life Space Dynamics by C. I. Ildarhanova

“…The author brings value and cultural basis of changes in social actions of citizens of a modern village and traces the role of social and cultural environment on development of network processes in a rural territory. It is underlined how demographic resources of a rural society lead to the lost of relations that are formed on a community type rather than on a society type. …”
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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by RAHMAT, Munirul ula, Zara Yunizar

“…GRU, a deep learning-based recurrent neural network, processes sequential data using a gating mechanism, making it effective for capturing short-term price dynamics. …”
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SFSCDNet: A Deep Learning Model With Spatial Flow-Based Semantic Change Detection From Bi-Temporal Satellite Images by K. S. Basavaraju, N. Sravya, Vibha Damodara Kevala, Shilpa Suresh, Shyam Lal

“…To overcome these limitations, this paper proposes a novel network called the Spatial Flow-based Semantic Change Detection Network. This network processes bi-temporal satellite images using a dual-encoder, triple-decoder architecture that progressively refines spatial features at each network stage, improving semantic change detection results. …”
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