PneuDetect: Pneumonia Detection using a Novel Two-Stage Deep Learning Pipeline from Chest X-Rays – A Review
Keywords:
Design of experiments, Analysis, spectrum optimization, pricing, Taguchi method, screen design and item factorizationAbstract
Cognitive Radio Networks (CRNs) play a pivotal role in addressing the spectrum scarcity Challenge by enabling secondary users (SUs) to dynamically access underutilized spectrum bands while ensuring minimal interference with primary users (PUs). In this study, we propose a novel approach that leverages Design of Experiments (DoE) principles to optimize spectrum utilization in CRNs. The research work is carried out to optimize the resources depending on the price factor and the demand in the current scenario. In such case, the demand raises from the secondary users to utilize the frequency spectrum. The primary users take a decision on the design of the experiment. The research work is carried out by designing of experiments. In this research work, Taguchi method, screen design and item factorization are implemented to determine the pricing of the spectrum for utilization by the secondary users with reference to the availability and the prices. The approach ensures efficient utilization of available spectrum resources while maintaining PU protection.
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Elias Z. Tragos, Sherali Zeadally, Alexandros G. Fragkiadakis and Vasilious A. Siris, “Spectrum Assignment in Cognitive Radio Networks: A comprehensive Survey”, IEEE communications Surveys & Tutorials, 2012.
Siye Wang, Zhennyer Liu, Wen Biano Zhou, Yanjum Zang, Dake Liu, “Analysis of Dynamic Spectrum Management for Secondary Network”, Elsevier, 2015
J.L. Ponz-Tienda, V Yeper, E Pellicer and J Moreno- Flores, “The resource Levelling Problem with Multiple Resources using an Adaptive Genetic Algorithm”, Automation in Construction, Vol 29, PP 162-172, 2013.
Qingyou, Yan, Qian Zhang and Xin Zhou, “A Cost Optimization model for Multi-resource Levelling Problem without Project Duration Constraint”, Vol 2016, Discrete Dynamics in nature and Society Hindwai,2016.
Z Mao, X Wang, “Efficient Optimal and Suboptimal Radio Resource Allocation in OFDMA System”, IEEE Transaction Wireless Communication 7(2) 440-445, 2005.
Babatunde S Awoyemi, Bodhaswar T J Maharaj Attahire S Alfa, “Solving Resource Allocation Problem in Cognitive Radio Networks: A Survey”, EURASIP Journal on Wireless Communication and Networking, 2016.
R. Rom and M Sidi, “Multiple Access Protocols Performance and Analysis Network”, Springer Verlag, 1990.
Z bigniew Micralwicz, “Genetic Algorithm + Data Structures= Evolution Programs 3rd Edition, Verlag, 1996.
V Jayaraj, et al, “An Analysis of Genetic Algorithm and Tabu search Algorithm for Channel Optimization in Cognitive Adhoc Network”, Vol 3, Issue 7, July 2014, pg 60-69.
X-Sang : A new Metaheuristic bat-inspired Algorithm”, Nature inspired cooperative strategies for optimization(NISCO2010),PP 65-74,2010.
X-S He, W-J Ding and X-S Yang “Bat Algorithm based on Simulated Annealing and Gaussian Perturbations” Neural Computing and applications vol25, no 2 2014.
J. Elhachmi and Z. Guennom, “ Cognitive Radio Specturm Allocation using Genetic Algorithm”, EURASIP Journal of Online Engineering, Vol2016 no1,pp 1-11,2016.
P. E. Darney and I J Jacob,” Performance Enhancement of Cognitive Radio Network using the improved Fuzzy Logic”, Journal of Soft computing paradigm (JSCP) Vol 1, no. 02, PP 57-68,2019.
S Mishra, S. Sagnika and S. S. Singh, and B.S.P Mishra, “Spectrum Allocation in Cognitive Radio: A PSO-based approach”, Periodica Polytechnica Electrical Engineering and Computer Science, Vol63, no.1, PP 23-29, 2019.
Z-J. Teng, L -Y. Xie, H-L Chen and H. Zhang, “Applications Research of Chaotic Binary Particle Swarm Optimization Algorithm in Dynamic Spectrum Allocation”, Journal of Computers, Vol 31, no.4 PP 288-299,2020.
B. Padmanaban and S Sathiyamoorthy, “A metaheuristic Optimization model for spectral Allocation in Cognitive Radio Networks based on ant colony Algorithm (M-ACO), “Soft Computing Vol24 no 20, PP 1551-15560, 2020.
X. Cheng and M. Jiang, “Cognitive Radio Spectrum Assignment based on Artificial Bee Colony Algorithm”, in 2011 IEEE 13th International Conference on Communication Technology, 2011, PP 161-164, IEEE.
Suganthi, N., Meenakshi, S. Efficient spectrum allocation for secondary users in cognitive radio network using round robin priority algorithm along with reservation channels. J Ambient Intell Human Comput 14, 16715–16728 (2023). https://doi.org/10.1007/s12652-023-04682-x
Sedighi, H., Abbaspour, M. Optimal Spectrum Allocation Based on Primary User Activity Model in Cognitive Radio Wireless Sensor Networks. Wireless Pers Commun 118, 195–216 (2021). https://doi.org/10.1007/s11277-020-08009-3.
Yu Zhang, Jinting Wang, W. Li,WEIWAYNELI, Optimal Pricing Strategies in Cognitive Radio Networks With Heterogeneous Secondary Users and Retrials, Digital Object Identifier 10.1109/ACCESS.2019.2903085.
Vaduganathan L, Neware S, Falkowski-Gilski P, Divakarachari PB. Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks. Entropy (Basel). 2023 Aug 31;25(9):1285. doi: 10.3390/e25091285. PMID: 37761584; PMCID: PMC10528549.
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