Particle Swarm Optimization inspired by starling flock behavior

Swarm intelligence is a meta-heuristic algorithm which is widely used nowadays for efficient solution of optimization problems. Particle Swarm Optimization (PSO) is one of the most popular types of swarm intelligence algorithm. This paper proposes a new Particle Swarm Optimization algorithm called Starling PSO based on the collective response of starlings. Although PSO performs well in many problems, algorithms in this category lack mechanisms which add diversity to exploration in the search process. Our proposed algorithm introduces a new mechanism into PSO to add diversity, a mechanism which is inspired by the collective response behavior of starlings. This mechanism consists of three major steps: initialization, which prepares alternative populations for the next steps; identifying seven nearest neighbors; and orientation change which adjusts velocity and position of particles based on those neighbors and selects the best alternative. Because of this collective response mechanism, the Starling PSO explores a wider area of the search space and thus avoids suboptimal solutions. We tested the algorithm with commonly used numerical benchmarking functions as well as applying it to a real world application involving data clustering. In these evaluations, we compared Starling PSO with a variety of state of the art algorithms. The results show that Starling PSO improves the performance of the original PSO and yields the optimal solution in many numerical benchmarking experiments. It also gives the best results in almost all clustering experiments.     

Ensemble learning for protein multiplex subcellular localization prediction based on weighted KNN with different features

As an important attribute of proteins, protein subcellular location(s) can provide valuable information about their functions. Determining protein subcellular locations using experimental methods are usually expensive and time-consuming. Over the years, a variety of computational approaches have been developed to predict protein subcellular locations based on knowledge of known protein locations. However, the problem is inherently hard, especially for proteins that can exist at multiple subcellular locations. Further studies are still in great need in this area. In this paper, we propose an ensemble learning framework that utilizes a modified Weighted K-Nearest Neighbors (WKNN) as the basic learning algorithm. Two different types of features are considered and extracted from training data, which are based on protein amino acid compositions (Amphiphilic Pseudo Amino Acid Composition, or AmPseAAC) and protein sequence similarities (Protein Similarity Measure, or PSM), respectively. Two individual classifiers are trained separately based on these two types of features and each assigns a probability distribution over different locations to a query protein. Based on the outputs of the two base classifiers, a novel ensemble strategy named Maximized Probability on Label (MPoL) is proposed. The strategy produces a final set of protein locations for each protein by integrating prediction results of the base classifiers through an optimization procedure. To measure the prediction quality of the proposed approach, two different types of evaluation metrics, example-based metrics and label-based metrics, are used. To evaluate the performance of our approach objectively, we compare its results with those predicted by another popular method named iLoc-Animal on a benchmark dataset through cross-validation. Results show that in terms of absolute true success rate on multi-location prediction, MPoL has achieved much better results than iLoc-Animal. It implies that the proposed method has some potential to solve a diverse set of multi-label learning problems.     

A Cellular Automata Based Verifiable Multi-secret Sharing Scheme Without a Trusted Dealer

—We proposed a verifiable multi-secret shar-ing scheme without a dealer. We use cellular automata, having the properties of linear computations and parallel computations, to construct our scheme. The linear com-putational property makes it possible to build a scheme without the assistance of a trusted dealer, and the parallel computational property contributes to the high efficiency of the scheme. Hash function is used to realize the verifica-tion of shares, which also makes our scheme more efficient. The security of the scheme is also analyzed.     

Novel way to research nonlinear feedback shift register

In this paper,we regard the nonlinear feedback shift register（NLFSR） as a special Boolean network,and use semi-tensor product of matrices and matrix expression of logic to convert the dynamic equations of NLFSR into an equivalent algebraic equation. Based on them,we propose some novel and generalized techniques to study NLFSR. First,a general method is presented to solve an open problem of how to obtain the properties（the number of fixed points and the cycles with different lengths） of the state sequences produced by a given NLFSR,i.e.,the analysis of a given NLFSR. We then show how to construct all 2^2^n-（l-n）/2^2^n-lshortest n-stage feedback shift registers（nFSR） and at least 2^2^n-（l-n）-1/2^2^n-l-1shortest n-stage nonlinear feedback shift registers（nNLFSR） which can output a given nonperiodic/periodic sequence with length l. Besides,we propose two novel cycles joining algorithms for the construction of full-length nNLFSR. Finally,two algorithms are presented to construct 2^2^n-2-1different full-length nNLFSRs,respectively.     

Verifiable database supporting keyword searches with forward security

The primitive of verifiable database (VDB) enables the integrity of database when a resource-limited client outsources a huge dynamic database on an untrusted cloud server. Meanwhile, the client could perform various types of queries on the database such as index-based queries and keyword-based queries. In the real-world applications, it is more suitable to consider VDB schemes supporting full updating operations (i.e., replacement, insertion, and deletion). Inherently, forward/backward-secure searchable encryption schemes should be adopted to incorporate VDB schemes. In this paper, we first attempt to address the problem of how to perform forward-secure keyword searching on VDB schemes. Moreover, we present a concrete VDB construction that can support forward-secure keyword search and full updating operations. Security and efficiency analysis demonstrate that the proposed VDB schemes can achieve the desired security properties with high efficiency.     

基于编码器的石油套管超声探伤系统探头随动控制实现

根据钢管超声探伤系统对于超声探头实时随动控制的实际功能要求和现场安装情况,采用编码器和到位开关,通过程序控制,实现了钢管超声探伤系统探头相对于钢管运动的随动控制功能.减小了钢管超声探伤系统探测盲区,保证了钢管超声探伤系统的探伤精度和提高了探伤效率.     

Depth map enhancement based on color and depth consistency

Current low-cost depth sensing techniques, such as Microsoft Kinect, still can achieve only limited precision. The resultant depth maps are often found to be noisy, misaligned with the color images, and even contain many large holes. These limitations make it difficult to be adopted by many graphics applications. In this paper, we propose a computational approach to address the problem. By fusing raw depth values with image color, edges and smooth priors in a Markov random field optimization framework, both misalignment and large holes can be eliminated effectively, our method thus can produce high-quality depth maps that are consistent with the color image. To achieve this, a confidence map is estimated for adaptive weighting of different cues, an image inpainting technique is introduced to handle large holes, and contrasts in the color image are also considered for an accurate alignment. Experimental results demonstrate the effectiveness of our method.     

Robust palmprint identification based on directional representations and compressed sensing

In this paper, we propose a novel approach for palmprint recognition, which contains two interesting components: directional representation and compressed sensing. Gabor wavelets can be well represented for biometric image for their similar characteristics to human visual system. However, these Gabor-based algorithms are not robust for image recognition under non-uniform illumination and suffer from the heavy computational burden. To improve the recognition performance under the low quality conditions with a fast operation speed, we propose novel palmprint recognition approach using directional representations. Firstly, the directional representation for palmprint appearance is obtained by the anisotropy filter, which is robust to drastic illumination changes and preserves important discriminative information. Then, the principal component analysis (PCA) is used for feature extraction to reduce the dimensions of the palmprint images. At last, based on a sparse representation on PCA feature, the compressed sensing is used to distinguish palms from different hands. Experimental results on the PolyU palmprint database show the proposed algorithm have better performance than that of the Gabor based methods.     

求解多段图问题的并行动态规划算法

多段图问题是一类特殊的单源最短路径问题。在串行动态规划算法的两种实现方法的基础上,根据图中顶点的编号,提出两种在集群环境下进行任务分割的并行化求解方法,并使用MPI进行实现。实验结果表明,所提出的算法具有较高的加速比和较低的通信复杂度、时间复杂度。算法不限于某种结构的集群,通用性强。     

Four-mobile-beacon assisted localization in three-dimensional wireless sensor networks

Localization is one of key technologies of wireless sensor networks, and the mobile beacon assisted localization method is promising. For the three-dimensional sensor networks, this paper proposes a four-mobile-beacon assisted weighted centroid localization method. The four beacons form a regular tetrahedron while traversing the region and broadcast packets including their positions simultaneously. The ordinary sensor nodes estimate their locations using weighted centroid method. It also presents Layered-Scan trajectory of mobile beacons which consists of several parallel layers of Scan. This method can localize all the sensor nodes with appropriate parameters. Two sets of simulations are performed using Matlab to compare this method with other methods and evaluate tradeoffs between localization performance and different parameters. Simulation results show that the proposed method outperforms weighted centroid and multilateration methods using single mobile beacon.