H.264/AVC帧间预测编码模式快速选择算法

通过对H.264/AVC帧间预测模式选择的实验观测,发现最近采用的SKIP/DIRECT模式或者16×16宏块模式,和当前块的选择模式有着空间和时间上的关联。依据这一现象,提出了一种快速的帧间自适应宏块模式选择算法。从验证模型JM7.6上的实验结果来看,在保持图像编码质量,视频编码比特没有太大增加的情况下,该算法对变化不是很剧烈的视频序列,可节省近50%的编码时间,对变化较为剧烈的视频序列,亦可节省近10%的编码时间,降低了原标准在进行帧间预测时的复杂度,提高了编码器的工作效率。     

Computing handle and tunnel loops with knot linking

Many applications seek to identify features like ‘handles’ and ‘tunnels’ in a shape bordered by a surface, embedded in three dimensions. To this end, we define handle and tunnel loops on surfaces which can help identify these features. We show that a closed surface of genus g always has g handle and g tunnel loops induced by the embedding. For a class of shapes that retract to graphs, we characterize these loops by a linking condition with these graphs. These characterizations lead to algorithms for detection and generation of these loops. We provide an implementation with applications to feature detection and topology simplification to show the effectiveness of the method.     

2-Covered paths by a set of antennas with minimum power transmission range

In this paper we describe and solve the following geometric optimisation problem: given a set S of n points on the plane (antennas) and two points A and B, find the smallest radial range r∈^ℜ+ (power transmission range of the antennas) so that a path with endpoints A and B exists in which all points are within the range of at least two antennas. The solution to the problem has several applications (e.g., in the planning of safe routes). We present an O(nlogn) time solution, which is based on the second order Voronoi diagram. We also show how to obtain a path with such characteristics.     

Lévy flight artificial bee colony algorithm

Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.     

Fault diagnosis of nonlinear and large-scale processes using novel modified kernel Fisher discriminant analysis approach

It is pretty significant for fault diagnosis timely and accurately to improve the dependability of industrial processes. In this study, fault diagnosis of nonlinear and large-scale processes by variable-weighted kernel Fisher discriminant analysis (KFDA) based on improved biogeography-based optimisation (IBBO) is proposed, referred to as IBBO-KFDA, where IBBO is used to determine the parameters of variable-weighted KFDA, and variable-weighted KFDA is used to solve the multi-classification overlapping problem. The main contributions of this work are four-fold to further improve the performance of KFDA for fault diagnosis. First, a nonlinear fault diagnosis approach with variable-weighted KFDA is developed for maximising separation between the overlapping fault samples. Second, kernel parameters and features selection of variable-weighted KFDA are simultaneously optimised using IBBO. Finally, a single fitness function that combines erroneous diagnosis rate with feature cost is created, a novel mixed kernel function is introduced to improve the classification capability in the feature space and diagnosis accuracy of the IBBO-KFDA, and serves as the target function in the optimisation problem. Moreover, an IBBO approach is developed to obtain the better quality of solution and faster convergence speed. On the one hand, the proposed IBBO-KFDA method is first used on Tennessee Eastman process benchmark data sets to validate the feasibility and efficiency. On the other hand, IBBO-KFDA is applied to diagnose faults of automation gauge control system. Simulation results demonstrate that IBBO-KFDA can obtain better kernel parameters and feature vectors with a lower computing cost, higher diagnosis accuracy and a better real-time capacity.     

A deadlock-free routing algorithm for dynamically reconfigurable Networks-on-Chip

We address routing in Networks-On-Chip (NoC) architectures that use irregular mesh topologies with Long-Range Links (LRL). These topologies create difficult conditions for routing algorithms, as standard algorithms assume a static, regular link structure and exploit the uniformity of regular meshes to avoid deadlock and maintain routability. We present a novel routing algorithm that can cope with these irregular topologies and adapt to run-time LRL insertion and topology reconfiguration. Our approach to accommodate dynamic topology reconfiguration is to use a new technique that decomposes routing relations into two stages: the calculation of output ports on the current minimal path and the application of routing restrictions designed to prevent deadlock. In addition, we present a selection function that uses local topology data to adaptively select optimal paths.The routing algorithm is shown to be deadlock-free, after which an analysis of all possible routing decisions in the region of an LRL is carried out. We show that the routing algorithm minimises the cost of sub-optimally placed LRL and display the hop savings available. When applied to LRLs of less than seven hops, the overall traffic hop count and associated routing energy cost is reduced. In a simulated 8 × 8 network the total input buffer usage across the network was reduced by 6.5%.     

Modeling and implementation of classification rule discovery by ant colony optimisation for spatial land-use suitability assessment

This paper presents an integrated modeling method for multi-criteria land-use suitability assessment (LSA) using classification rule discovery (CRD) by ant colony optimisation (ACO) in ArcGIS. This new attempt applies artificial intelligent algorithms to intelligentise LSA by discovering suitability classification rules. The methodology is implemented as a tool called ACO-LSA. The tool can generate rules which are straightforward and comprehensible for users with high classification accuracy and simple rule list in solving CRD problems. A case study in the Macintyre Brook Catchment of southern Queensland in Australia is proposed to demonstrate the feasibility of this new modeling technique. The results have addressed the major advantages of this novel approach.     

基于在线社会网络的网络协议增强机制研究

在线社会网络已得到广泛应用,综合利用在线社会网络的社会关系信息和拓扑特征可以明显增强各层网络协议功能、性能和安全特性而使其成为新的研究热点。主要研究基于在线社会网络的网络协议增强机制,在分析现有增强机制特点的基础上,对它们进行了分类。然后,深入分析了各类增强机制的关键技术,总结相关研究存在的不足,最后提出一种集成社会感知平面的网络协议增强模型。     

网络拓扑结构的数学模型及遗传算法

提出了网络拓扑结构的定义。 以ATM网络问题为例建立了优化问题的数学模型,并描述了用遗传算法并行求解该问题的方法。该方法较圆满地解决了既考虑经济效益又考虑需求的ATM网络问题。该问题的研究对实际应用及推动动态网络的研究有十分重要的意义。     

A Constraint-Based Approach for Deriving 3-D Structures of Cyclic Polypeptides

This paper presents an hybrid algorithm for deriving 3-D structures of cyclic polypeptides. The algorithm combines constraint-based techniques with the most widely used methods for non-cyclic polypeptides. The empirical results demonstrate that the proposed hybrid algorithm outperforms traditional methods especially with respect to running times.