According to the characteristics of picking working in automated warehouse, a storage/retrieval scheduling optimization problem of a stacker crane is studied. The mathematic model of the order picking optimization is given based on two operation modes of a stacker crane, i.e. single access mode and combined access mode, and realized by means of the optimized Dijkstra algorithm, which makes it more intellectually to search path approaching to the target node and reduces traversing nodes. Experimental results show that this strategy can reduce the working distances of the stacker crane and promotes the efficiency of the automated warehouse.

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In the trust management scheme of the distributed cognitive radio networks, the absence of the central control devices cause many problems such as a lack of standardized control for trust computation, and the absence of the decision makers in trust evaluation and collaborative decision making. A trust management mechanism based on the jury system for distributed cognitive radio networks is proposed in this paper. The "jury user" is designed to collaboratively examine the reputation of the cognitive user in the networks and to perform data fusion and spectrum allocation for distributed cognitive radio networks. Simulation analysis results show that the proposed scheme can ensure accuracy and fairness in trust evaluation and improve effectiveness and flexibility of spectrum allocation.

With the reversible data hiding method based on pixel-value-ordering, data are embedded through the modification of the maximum and minimum values of a block. A significant relationship exists between the embedding performance and the block size. Traditional pixel-value-ordering methods utilize pixel blocks with a fixed size to embed data; the smaller the pixel blocks, greater is the embedding capacity. However, it tends to result in the deterioration of the quality of the marked image. Herein, a novel reversible data hiding method is proposed by incorporating a block merging strategy into Li et al.'s pixel-value-ordering method, which realizes the dynamic control of block size by considering the image texture. First, the cover image is divided into non-overlapping 2×2 pixel blocks. Subsequently, according to their complexity, similarity and thresholds, these blocks are employed for data embedding through the pixel-value-ordering method directly or after being emerged into 2×4, 4×2, or 4×4 sized blocks. Hence, smaller blocks can be used in the smooth region to create a high embedding capacity and larger blocks in the texture region to maintain a high peak signal-to-noise ratio. Experimental results prove that the proposed method is superior to the other three advanced methods. It achieves a high embedding capacity while maintaining low distortion and improves the embedding performance of the pixel-value-ordering algorithm.