Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Oleg Igorevich Rozhdestvenskiy"'
Autor:
Ravi Prakash Babu Kocharla, Siva Sankara Babu Chinka, Murahari Kolli, Satyanarayana Kosaraju, Oleg Igorevich Rozhdestvenskiy, Ankita Joshi, Muntather Almusawi
Publikováno v:
Cogent Engineering, Vol 11, Iss 1 (2024)
Laminated composites are generally made up of fibers reinforced using a polymer matrix. However, the delamination of such composites necessitates the incorporation of small quantities of nanoparticles to enhance the strong adhesion between the reinfo
Externí odkaz:
https://doaj.org/article/65c9b5c206174c64be18b227b4e8ac88
Autor:
Murahari Kolli, Kosaraju Satyanarayana, Mechiri Sandeep Kumar, A. Varun, Solovev S. A, Oleg Igorevich Rozhdestvenskiy, Anil Kumar Saxena
Publikováno v:
Cogent Engineering, Vol 11, Iss 1 (2024)
Aluminum metal matrix composites (MMCs) are a distinct class of materials with better performance characteristics than their equivalents made entirely of metal. The structural, maritime, aviation, defense and mining sectors all make extensive use of
Externí odkaz:
https://doaj.org/article/4bb82e96d00d498ba43b0ff812a97d6b
Autor:
Mahendra Varma Polakonda, Naga Ramadevi Vedala, Rajyalakshmi Kottapalli, Soloveva O.V, Oleg Igorevich Rozhdestvenskiy, Ankita Joshi
Publikováno v:
Cogent Engineering, Vol 11, Iss 1 (2024)
The present paper explains the performance of a production process of finite capacity for two classes of customers who may exhibit impatience. The arrivals can be found in terms of batches and will be picked for service in FIFO mode. The production r
Externí odkaz:
https://doaj.org/article/a003cd803b494bf6aaec00e0ba22b0c0
Artificial neural network-based clustering in Wireless sensor Networks to balance energy consumption
Autor:
Padmalaya Nayak, Veena Trivedi, Surbhi Gupta, Phaneendra Babu Booba, Soloveva O.V, Oleg Igorevich Rozhdestvenskiy, Ankita Joshi
Publikováno v:
Cogent Engineering, Vol 11, Iss 1 (2024)
The stability of Wireless Sensor Networks (WSNs) is a crucial requirement in real-time applications such as military, defense, and other surveillance systems. Clustering in WSNs is one of the most predominant techniques, offering benefits such as min
Externí odkaz:
https://doaj.org/article/9adaa5c34070434880ee083b99a24e0b
Autor:
Lipika Goel, Neha Nandal, Sonam Gupta, Madhavi Karanam, Lakshmi Prasanna Yeluri, Alok Kumar Pandey, Oleg Igorevich Rozhdestvenskiy, Pyotr Grabovy
Publikováno v:
Cogent Engineering, Vol 11, Iss 1 (2024)
Demand forecasting, a crucial aspect of anticipating future customer needs, involves using historical data to predict trends. With the rise of artificial intelligence (AI), companies are increasingly turning to machine learning algorithms to enhance
Externí odkaz:
https://doaj.org/article/90dae623ce64491da05be304e13d6333