This paper deals with the event-triggeredH∞asynchronous secure control problem for piecewise homogeneous Markov jump systems (PHMJSs) with denial-of-service (DoS) attacks and mode-dependent deception attacks. With the aid of acknowledgement character technique and probabilistic threshold division method, a mode-dependent switching-like probabilistic event-triggered mechanism is established to save communication resources while remedying the adverse effects of both DoS attack-induced packet losses and stochastic fluctuation of the triggering threshold on PHMJSs. Sufficient criteria are developed to ensure the stochastic stability andH∞performance of PHMJSs with hybrid cyber-attacks. It analytically builds the relationship between the maximum number of consecutive packet losses induced by DoS attacks and the triggering parameter. A co-design scheme is provided to calculate the event-triggering weight matrices and controller gains. Ultimately, an application-oriented example of the F-404 aircraft engine system is offered to demonstrate the validity of the proposed approach.

Ground-penetrating radar (GPR), as a geophysical survey method, offers high resolution and fast detection capabilities obtaining rich information about the underground structure. However, under real conditions, GPR is susceptible to interference and clutter. Therefore, there is an urgent need to develop methods for suppressing clutter, highlighting and positioning targets in GPR images. This article proposed an integrated method consisting of two modules: GPR image decluttering and underground target localization, which are used for clutter suppression and hyperbola vertex estimation from GPR image. In the first module, an unsupervised generative adversarial network (GAN) model is developed to map cluttered GPR images to clutter-free GPR images, where the CycleGAN is adapted as the main network architecture. To further improve the performance of the model, the first module proposes a novel loss function that introduces a perceptual loss into the previous CycleGAN loss. It utilizes a multiscale structural similarity index (MS-SSIM) loss to obtain richer and more realistic context information. In the second module, based on the obtained decluttered image, a novel adaptive target characterization algorithm, called gradient points clustering-based localization (GPCL), is proposed for the recognition and localization of GPR target signatures. This algorithm is designed to leverage changes in target position and local characteristics, thereby achieving efficient target vertex evaluation. Experimental results conducted on field datasets demonstrate that the proposed methods can significantly improve the quality and clarity of various cluttered images and exhibit strong applicability for the localization of underground targets.

The security problem for a kind of switched nonlinear systems with denial-of-service (DoS) attacks is addressed here with a novel event-triggered neural network (NN) adaptive control technique. The provided event-triggered control algorithm, compared to the current output feedback control schemes on continuous-time systems, not only conserves communication resources but also defends against DoS attacks throughout the system stabilization process. First, a novel adaptive NN switching observer is proposed by examining the stability of each subsystem in the sleep and active intervals of the attack, which makes the standard backstepping controller workable even in the DoS attacks scenario. Further, an event-triggered secure control strategy is established by creating a common coordinate transformation, which ensures the bound of all the signals in the resultant system under arbitrary switching and prevents the occurrence of Zeno behavior. A first-order filter is developed to fix the complexity explosion problem in backstepping design. Finally, a continuous stirred tank reactor example is presented to support the established method.

This article investigates the finite time bumpless transfer fuzzy control problem for Markovian jump fuzzy systems (MJFSs) via an observer-based bumpless transfer fuzzy control approach. Neither the measurability of system states nor the availability of all transition rates for each subsystem is required. A bumpless transfer index with a continuous reference input is derived to characterize the transient jumping behavior of MJFSs caused by an observer-based fuzzy jumping controller. First, a Markovian jump fuzzy model is employed to describe the more general practical situations. Second, by introducing a fuzzy state observer, an observer-based bumpless transfer fuzzy jumping controller is established, and a sufficient condition is developed such that the finite time fuzzy control issue for MJFSs is solvable while ensuring the bumpless transfer index. Finally, two simulation examples are provided to verify the utilizability of the acquired method.

BACKGROUND: Long non-coding RNA (lncRNA) studies play an important role in the development, invasion, and metastasis of the tumor. The analysis and screening of the differential expression of lncRNAs in cancer and corresponding paracancerous tissues provides new clues for finding new cancer diagnostic indicators and improving the treatment. Predicting lncRNA-protein interactions is very important in the analysis of lncRNAs. This article proposes an Ant-Colony-Clustering-Based Bipartite Network (ACCBN) method and predicts lncRNA-protein interactions. The ACCBN method combines ant colony clustering and bipartite network inference to predict lncRNA-protein interactions. RESULTS: A five-fold cross-validation method was used in the experimental test. The results show that the values of the evaluation indicators of ACCBN on the test set are significantly better after comparing the predictive ability of ACCBN with RWR, ProCF, LPIHN, and LPBNI method. CONCLUSIONS: With the continuous development of biology, besides the research on the cellular process, the research on the interaction function between proteins becomes a new key topic of biology. The studies on protein-protein interactions had important implications for bioinformatics, clinical medicine, and pharmacology. However, there are many kinds of proteins, and their functions of interactions are complicated. Moreover, the experimental methods require time to be confirmed because it is difficult to estimate. Therefore, a viable solution is to predict protein-protein interactions efficiently with computers. The ACCBN method has a good effect on the prediction of protein-protein interactions in terms of sensitivity, precision, accuracy, and F1-score.

Fingerprint template protection has recently drawn much attention due to public security and privacy awareness. In this paper, we demonstrate an approach for designing a non-invertible fingerprint template by constructing the many-to-many bit-string polar transformations with different minutiae points. We explore the relative relationship of minutiae points in polar system, which is registration-free in practical implementations. The security is guaranteed by the non-invertibility of the polar transformations. The performance is evaluated for the merits of non-invertibility, accuracy, diversity and revocability using publicly available benchmark databases, FVC2002 (DB1, DB2) and FVC2004 (DB1, DB2). It shows that the proposed approach exhibits favorable performance compared with the state-of-art alignment-free cancelable fingerprint template protection scheme.

CT angiography image vessel segmentation technique plays a critical role in many practical applications such as diagnosis of diseases and surgical planning. Blood vessels after angiography are often defective in low contrast and high noise due to individual differences and limitations of imaging device. A set of segmentation methods has been proposed for such data feature, which firstly adopts combination of average filtering with high frequency emphasizes filtering enhancement algorithms to perform enhancement preprocessing on the original image, thereby enhancing the contrast ratio of blood vessels and surrounding area; secondly, it performs vessel extraction on the enhanced data using region growth algorithm to obtain the segmentation data of richer vessel branches. Experimental results prove that the segmentation approach proposed here can accurately perform vessel segmentation and effectively avoid incorrect segmentation with better robustness.

A quantum TITO (Two-Input-Two-Output) diversity transmission scheme for the entangled-state message is proposed by generalizing the wireless transmission technique to the quantum field. The TITO quantum teleportation can be implemented with non-maximally entangled Bell states in order to enhance the security and fidelity of the quantum channel, in which a quantum signal sequence with n entangled quantum states can be transmitted through the TITO quantum channel by applying the diversity technology. The analysis shows that the quantum TITO transmission can be achieved securely and with an expected fidelity.

A novel quantum anonymous communication scheme is proposed on the basis of Dining Cryptographers (DC) Problem and nonmaximally entangled qubit pair. The scheme takes advantage of quantum-mechanical impossibility of local unitary transformation between certain nonmaximally entangled states to provide truly random number which can be brightly used in anonymous communication protocols based on DC-Nets. The analysis and discussions demonstrate that the proposed quantum anonymous communication scheme can be performed securely with high capacity and untraceability. The scheme can also be extended to a (2, 2) quantum secret sharing (QSS) scheme.

A novel (n, n) scheme of multiparty quantum group signature of classical or quantum message is proposed based on the discrete quantum Fourier transform. The generation and verification of the signature can be processed only if all the n participants work in concert. Moreover, a new verification manner, in which the message owner and the signing group separately verify the signature on both side by using the entangled state of EPR sequence, is involved in this paper. Security analysis shows that it is feasible to achieve a secure quantum group signature with the secure quantum computation.