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The accuracy of the resonant frequency servo loop is a major concern for the high-performance operation of a resonant fiber optic gyro. For instance, a bias error as large as tens or even hundreds of degrees/hour has been observed at the demodulated output of the resonant frequency servo loop. The traditional frequency servo mechanism is not an efficient tool to address this problem. In our previous work, we proposed a novel method to minimize the laser frequency noise to the level of the shot noise by refractive index modulation by a thermally tunable resonator. In this paper, we performed the parameter optimization for the resonator coil, multifunction integrated-optics chip, and couplers by the transition matrix using the Jones matrix methodology to minimize the polarization error. With the optimized parameter values, we achieved the bias value of the resonator fiber optic gyro to 1.924°/h.

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Delay elements are added in wave-pipelined circuit to improve the performance of the circuit by reducing the delay difference of the longest and the shortest paths. But it is very difficult to obtain exact delay needed in the circuit. Instead in the present system Interrupt logic is used for delay balancing, thereby providing more feasible and accurate circuit path.

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Patients’ medical data are extremely sensitive information during storage and transfer, and it needs the highest security level. Furthermore, these records must frequently be linked to patient medical data, and then the linked medical data are securely transmitted to the healthcare center. In this study, a Blockchain-Based Traceable Data Sharing method is proposed to securely transfer the medical data. A Paillier homomorphic encryption method is used to prevent data theft or attacks from occurring in the cloud as a result of the transfer of medical data there. It prevents intravenous third parties, which executes arithmetic operations on the ciphertext. Then the encrypted data are stored in the cloud and to remove clone nodes in the gateway, a software-defined networking technology is introduced. Then a Blockchain-Based Traceable Data Sharing is proposed to ensure data privacy and authenticity while maintaining data privacy at the point of data transmission. Data are then encrypted using a new Enhanced Cipher Text-Policy Encryption Attribute-based Encryption (E-CP-ABE). Private blockchain transfers are carried out on the chain, supporting fine-grain access control with flexible access policies and creating a private key in E-CP-ABE. The presented technique is executed in Matlab software of version R2020a. The performance parameters are encryption, and decryption time, mean square error (MSE), peak signal-to-noise ratio (PSNR), sensitivity, respectively. The encryption process function is nearly 8% superior than the existing methods and the decryption time is 14% greater than other methods. As a result, this study shows that the research approach outperformed in terms of encryption time and decryption time, as well as PSNR, MSE, and sensitivity. This technique outperforms other state-of-the-art algorithms in terms of imperceptibility and robustness against various attacks. Consequently, this approach is more reliable than previous methods for the transmission of medical data.

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