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Cancelable biometrics is a powerful remedy for information leakage caused by the extensive usage of unprotected biometric data. Current measures usually suffer from deteriorated accuracy, which is known as the security–performance tradeoff. Motivated by these concerns, in this article, a novel cancelable fingerprint approach, i.e., Indexing-Min–Max (IMM) hashing, is proposed to securely transform a fixed-length fingerprint feature vector to a discrete index hashed code. IMM hashing is essentially established upon the min–max hash and further strengthened by the integration of the partial Hadamard transform, which alleviates performance deterioration while maintaining a high security level. Extensive experiments on FVC2002 and FVC2004 fingerprint datasets coupled with comprehensive theoretical analyses demonstrate the favorable accuracy and strong anti-attack resilience of the proposed method. Besides, compared to the unprotected counterpart, the matching precision of the protected templates yields little accuracy loss or even improved performance, which means the security–performance tradeoff is well handled. Furthermore, IMM hashing also meets the unlinkability and revocability requisites of cancelable biometrics. [ABSTRACT FROM AUTHOR]

Rotary ultrasonic machining (RUM) is a superior technology to machine hard and brittle materials. Traditionally, the compensation optimization for the RUM system is limited to a single resonant frequency. This article presents a novel double compensation approach for the impedance and frequency regulations of RUM via multiobjective genetic algorithm (MOGA) aiming to achieve the system resonance and monitor the machining process in real time. For this, we first establish the impedance model of the rotary ultrasonic holder (RUH) by adopting the T-type circuit that includes the comprehensive electromagnetic parameters. The obtained impedance model reveals that both frequency mismatch and impedance mismatch exist in the RUM system, causing the low voltage gain and low vibration transmission. To obtain the optimal compensation to match both the frequency and impedance, an optimization model-based MOGA is developed to intelligently search the accurate capacitance values, where the Pareto frontier is employed to visualize the capacitance solution distribution. Moreover, the response feature of the RUH system is attained by using the state-space equation. Detailed comparisons of four compensation topologies show that the series–series (SS) topology offers the optimal performance, which can match both of the frequency and the impedance well, improving the output active power 7.634 times compared to the conventional one. Finally, the validity of the proposed optimization method is confirmed by using both simulations and experiments. Note to Practitioners—This article was motivated by the transmission efficiency and the stability of ultrasonic vibration in the rotary ultrasonic machining (RUM). The matching issue is critical in RUM because the whole system is very complicated with multiple components such as electrical devices, piezoelectric rings, and mechanical horn. In the conventional RUM, the system matching is limited to a single resonant frequency between the piezoelectric transducer and the electrical driver. However, the impedance matching is also important to influence the ultrasonic vibration. The problem of the ultrasonic matching stems from empirical experiences of the engineers’ or simple heuristic rules instead of advanced approaches. On the other hand, optimization-based techniques are viewed as a great success in industrial and engineering applications. With the assistance of our proposed numerical model and the corresponding simulation, we found that the multiobjective genetic algorithm (MOGA) can intelligently search the optimal compensated parameters to achieve the double matching for both the resonant frequency and the impedance in the RUM system. Finally, our experiments prove that the MOGA optimization can attain optimal transmission efficiency for the electrical voltage and current compared with conventional approaches. This significantly benefits the application of the RUM technology in industry, especially for the precision machining of the hard and brittle materials. [ABSTRACT FROM AUTHOR]