Genetic programming for QoS-aware web service composition and selection

Web services, which can be described as functionality modules invoked over a network as part of a larger application are often used in software development. Instead of occasionally incorporating some of these services in an application, they can be thought of as fundamental building blocks that are combined in a process known as Web service composition. Manually creating compositions from a large number of candidate services is very time consuming, and developing techniques for achieving this objective in an automated manner becomes an active research field. One promising group of techniques encompasses evolutionary computing, which can effectively tackle the large search spaces characteristic of the composition problem. Therefore, this paper proposes the use of genetic programming for Web service composition, investigating three variations to ensure the creation of functionally correct solutions that are also optimised according to their quality of service. A variety of comparisons are carried out between these variations and two particle swarm optimisation approaches, with results showing that there is likely a trade-off between execution time and the quality of solutions when employing genetic programming and particle swarm optimisation. Even though genetic programming has a higher execution time for most datasets, the results indicate that it scales better than particle swarm optimisation.     

A novel recommendation approach based on users’ weighted trust relations and the rating similarities

With the growing popularity of open social networks, approaches incorporating social relationships into recommender systems are gaining momentum, especially matrix factorization-based ones. The experiments in previous literatures indicate that social information is very effective in improving the performance of traditional recommendation algorithms. However, most of existing social recommendation methods only take one kind of social relations—trust information into consideration, which is far from satisfactory. Furthermore, most of the existing trust networks are binary, which results in the equal treatment to different users who are trusted by the same user in these methods. In this paper, based on matrix factorization methods, we propose a new approach to make recommendation with social information. Its novelty can be summarized as follows: (1) it shows how to add different weights on the social trust relationships among users based on the trustee’s competence and trustworthiness; (2) it incorporates the similarity relationships among users as a complement into the social trust relationships to enhance the computation of user’s neighborhood; (3) it can balance the influence of these two kinds of relationships based on user’s individuality adaptively. Experiments on Epinions and Ciao datasets demonstrate that our approach outperforms the state-of-the-art algorithms in terms of mean absolute error and root mean square error, in particular for the users who rated a few items.     

One-step implementation of a Toffoli gate of separated superconducting qubits via quantum Zeno dynamics

Based on the quantum Zeno dynamics, a scheme is presented to implement a Toffoli gate of three separated superconducting qubits (SQs) by one step. Three separated SQs are connected by two resonators. The scheme is insensitive to the resonator decay because the Zeno subspace does not include the state of the resonators being excited. Numerical simulations indicate that the scheme is robust to the fluctuation of the parameters and the Toffoli gate can be implemented with high fidelity.     

An efficient algorithm for the tensor product model transformation

The tensor-product (TP) model transformation was proposed recently as a numerical and automatically executable method which is capable of transforming linear parameter varying (LPV) state-space models into the higher order singular value decomposition (HOSVD) based canonical form of polytopic models. The crucial disadvantage of the TP model transformation is that its computational load explodes with the density of discretization and the dimensionality of the parameter vector of the parameter-varying state-space model. In this paper we propose a new algorithm that leads to considerable reduction of the computation in the TP model transformation. The main idea behind the modified algorithm is to minimize the number of discretized points to acquire as much information as possible. The modified TP model transformation can readily be executed on a regular computer efficiently and concisely, especially in higher dimensional cases when the original TP model transformation fails. The paper also presents numerical examples to show the effectiveness of the new algorithm.     

机载雷达级联降维空时自适应杂波抑制方法

提出一种机载雷达杂波抑制的级联降维空时自适应算法,即,先对全空时两维接收数据进行预滤波处理,将杂波局域化,降低杂波自由度;然后对预处理输出的信号的相关矩阵进行子阵划分,求解低维权向量,进一步降低运算量和采样要求。理论分析和实验仿真结果表明,所提算法具有良好的收敛性能和杂波抑制能力,并且对于阵元随机幅相误差和杂波起伏具有很好的容差能力。基于实测数据的实验验证了算法的有效性和稳健性。     

面向中小企业的电商平台挖掘系统设计

中小企业电商平台在资金和技术不足的情况下,难以快速有效的构建简单而实用的电商数据挖掘系统.文章从分析电商海量数据资源的来源、提取方法及其流程入手,提出了一个基本的数据挖掘系统方案架构,从而实现为中小企业电商平台服务的一整套数据挖掘系统.该系统架构简单实用、易搭建、易整合,可以为中小企业提供更好的服务支持.     

音频、视频设备剩余电压检测技术研究

分析两种剩余电压测试方法—剩余电压测试仪法和数字存储示波器法的优、缺点,详细分析数字存储示波器法的输入阻抗、示波器供电电源、测试设备计量溯源等问题,并对最大剩余电压测量结果的不确定度进行分析评定,尽量减小各不确定度分量,以保证最高剩余电压的检测结果准确可靠。     

浅谈葛铺矿综合自动化环网平台建设和使用情况

根据我国当前工业自动化的发展成果、葛铺矿工业环网的建设需求、矿井井下巷道的分布结构和矿井未来发展的需要,从MACH-4002核心交换机的选取到系统VLAN划分方式等方面,综述了葛铺矿综合自动化环网平台的建设方案,并阐述了环网平台的使用情况。