An efficient threshold key-insulated signature scheme

To tackle the key-exposure problem in signature settings, this paper introduces a new cryptographic primitive named threshold key-insulated signature (TKIS) and proposes a concrete TKIS scheme. For a TKIS system, at least k out of n helpers are needed to update a user’s temporary private key. On the one hand, even if up to k−1 helpers are compromised in addition to the exposure of any of temporary private keys, security of the non-exposed periods is still assured. On the other hand, even if all the n helpers are compromised, we can still ensure the security of all periods as long as none of temporary private keys is exposed. Compared with traditional key-insulated signature (KIS) schemes, the proposed TKIS scheme not only greatly enhances the security of the system, but also provides flexibility and efficiency.     

Comparison of osteogenesis between two kinds of stem cells from goat combined calcium phosphate cement in tissue engineering

To explore the possible mechanism of osteogenesis for deciduous teeth stem cells (DTSCs) in vivo/ vitro, stem cells from goat deciduous teeth (SGDs) were firstly isolated, induced and transplanted into immunocompromised mice. The SGDs’s mineralization pattern and osteogenesis were compared with bone marrow messenchymal stem cells (BMMSCs) from goats. SGDs have similar osteogenic differentiation pattern in vitro and bone-like tissue formation mechanism in vivo to BMMSCs; moreover SGDs have stronger alkaline phosphatase (ALP) gene expression and osteopontin (OPN) gene expression levels than BMMSCs; also SGDs can form more bone-like tissues than BMMSCs when cell-scaffold compounds are transplanted into immunocompromised mice. This pre-clinical study in a large-animal model confirms that DTSCs may be an appropriate source of stem cells in repairing bone defects with tissue engineering.     

Identity-based threshold decryption on access structure

For the applied limitation of the existing threshold decryption schemes based on the (t, n) structure, an identity-based threshold decryption scheme which can be applied on the access structure is proposed through designing a special distribution algorithm of the private key shares. The generation and distribution of private key shares, the encryption, the decryption and the combination are introduced in detail. The validity and security of the scheme are proved and analyzed. Comparisons with the existing schemes show that the proposed scheme is more flexible.     

Three-dimensional numerical simulation of splat formation on substrates in plasma spraying

Plasma sprayed coatings are built up by the accumulation of splats formed by the impacting, spreading and solidifying of molten droplets on the substrate. A three-dimensional computational model including heat transfer and solidification is established to simulate the formation process of a single splat using the computational fluid dynamics (CFD) software, FLUENT. The fluid flow and energy equations are discretized and solved according to typical finite volume method on an unstructured grid. A volume of fluid (VOF) tracking algorithm is used to track the droplet flow with free surface. In order to understand the splat formation mechanism, the process of splat formation caused by impacting and spreading of a molten nickel droplet on a polished mild steel surface is simulated. On this basis, the simulations of impact of a molten droplet on substrate with different conditions including the surface morphology, thermal conductivity, initial temperature of the substrate and the thermal contact resistance are presented. The results clearly show the effect of those parameters on the shape of the final splat and splash behaviors.     

Implementation of dynamic matrix control on field programmable gate array

High performance computer is often required by model predictive control (MPC) systems due to the heavy online computation burden. To extend MPC to more application cases with low-cost computation facilities, the implementation of MPC controller on field programmable gate array (FPGA) system is studied. For the dynamic matrix control (DMC) algorithm, the main design idea and the implemental strategy of DMC controller are introduced based on a FPGA’s embedded system. The performance tests show that both the computation efficiency and the accuracy of the proposed controller can be satisfied due to the parallel computing capability of FPGA.     

Study on bending conditions of plate in coil box

In a coil box between the roughing and finishing stands on a hot strip mill, a problem has been encountered that the entry region of the plate touches the bending rolls and deforms. As a result, the defective coil occurs. The condition of plate bending, which forms a new deformation feature in coiling, is analyzed. In this paper, the authors focus on the research of the effects of coiling parameters, such as the thickness of plate, roll speed and feeding speed of plate in coil box, and on specific plate bending. A finite element method is developed to simulate this coiling process. Based on numerical simulation, the effects of the coiling parameters on the mechanics and deformation of the bending plate are obtained. Numerical simulation tests have verified the validity of the developed model.     

Chaff cloud jamming suppression based on wavelet transform

Radar target signals and chaff cloud jamming signals have different characters by the wavelet transform. The wavelet coefficients of radar target signals are highly correlated with its near-and-near-scale wavelet coefficients, however the correlativity between the wavelet coefficients of chaff cloud jamming signals and its near-and-near scale wavelet coefficients is less significant. Based on the binary-base discrete wavelet transform and the correlation algorithm, the method of target entropy to estimate standard variance of the jamming signals and each scale is proposed to ensure reasonable threshold, to suppress chaff cloud signals and finally to reconstruct mixed signals by the improved spatially selective noise filtration (ISSNF) method. The extensive simulation results show that the proposed method can availably suppress chaff cloud jamming and decontaminate target echo.     

Reputation-based collaborative spectrum sensing scheme in cognitive radio networks

Collaborative spectrum sensing is proposed to improve the detection performance in cognitive radio (CR) networks. However, most of the current collaborative sensing schemes are vulnerable to the interference of the malicious secondary users (SUs). In this paper we propose a reputation-based collaborative spectrum sensing scheme to improve the security of cooperative sensing by mitigating the impacts of misbehaviors. The fusion center calculates the reputation rating of each SU according to their history reports to weight their sensing results in the proposed scheme. We analyze and evaluate the performance of the proposed scheme and its advantages over previous schemes in expansibility and integrity. Simulation results show that the proposed scheme can minimize the harmful influence from malicious SUs.     

Fault diagnosis for singular stochastic systems

This paper studies the fault diagnosis of singular stochastic systems. The probability distribution of output is measured by probability density functions (PDFs), which are modeled by a square root B-spline expansion. An adaptive nonlinear observer is proposed to estimate the size of the fault occurring in systems. Furthermore, the linear matrix inequality (LMI) approach is applied to establish sufficient conditions for the existence of the observer. Finally, the simulation results are given to indicate the method for diagnosing the fault.     

Automatic product image classification with multiple support vector machine classifiers

For the task of visual-based automatic product image classification for e-commerce, this paper constructs a set of support vector machine (SVM) classifiers with different model representations. Each base SVM classifier is trained with either different types of features or different spatial levels. The probability outputs of these SVM classifiers are concatenated into feature vectors for training another SVM classifier with a Gaussian radial basis function (RBF) kernel. This scheme achieves state-of-the-art average accuracy of 86.9% for product image classification on the public product dataset PI 100.