Muhammad Imran¹, Jinsheng Sun^1,*, Fatima Sehar Zaidi², Zameer Abbas^3,4, Hafiz Zafar Nazir⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1207-1257, 2023, DOI:10.32604/cmes.2023.025492

Abstract Control charts (CCs) are one of the main tools in Statistical Process Control that have been widely adopted in manufacturing sectors as an effective strategy for malfunction detection throughout the previous decades. Measurement errors (M.E’s) are involved in the quality characteristic of interest, which can effect the CC’s performance. The authors explored the impact of a linear model with additive covariate M.E on the multivariate cumulative sum (CUSUM) CC for a specific kind of data known as compositional data (CoDa). The average run length is used to assess the performance of the proposed chart. The results indicate that M.E’s significantly… More >

H. Anandakumar^a, K. Umamaheswari^b

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 843-849, 2018, DOI:10.1080/10798587.2017.1364931

Abstract Cognitive radio systems necessitate the incorporation of cooperative spectrum sensing among cognitive users to increase the reliability of detection. We have found that cooperative spectrum sensing is not only advantageous, but is also essential to avoid interference with any primary users. Interference by licensed users becomes a chief concern and issue, which affects primary as well as secondary users leading to restrictions in spectrum sensing in cognitive radios. When the number of cognitive users increases, the overheads of the systems, which are meant to report the sensing results to the common receiver, which becomes massive. When the spectrum, which is… More >