A new decomposition based evolutionary algorithm with uniform designs for many-objective optimization

For many-objective optimization problems, how to get a set of solutions with good convergence and diversity is a difficult and challenging work. In this paper, a new decomposition based evolutionary algorithm with uniform designs is proposed to achieve the goal. The proposed algorithm adopts the uniform design method to set the weight vectors which are uniformly distributed over the design space, and the size of the weight vectors neither increases nonlinearly with the number of objectives nor considers a formulaic setting. A crossover operator based on the uniform design method is constructed to enhance the search capacity of the proposed algorithm. Moreover, in order to improve the convergence performance of the algorithm, a sub-population strategy is used to optimize each sub-problem. Comparing with some efficient state-of-the-art algorithms, e.g., NSGAII-CE, MOEA/D and HypE, on six benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence.     

On recommendation problems beyond points of interest

Recommendation systems aim to recommend items or packages of items that are likely to be of interest to users. Previous work on recommendation systems has mostly focused on recommending points of interest (POI), to identify and suggest top-k items or packages that meet selection criteria and satisfy compatibility constraints on items in a package, where the (packages of) items are ranked by their usefulness to the users. As opposed to prior work, this paper investigates two issues beyond POI recommendation that are also important to recommendation systems. When there exist no sufficiently many POI that can be recommended, we propose (1) query relaxation recommendation to help users revise their selection criteria, or (2) adjustment recommendation to guide recommendation systems to modify their item collections, such that the users׳ requirements can be satisfied.We study two related problems, to decide (1) whether the query expressing the selection criteria can be relaxed to a limited extent, and (2) whether we can update a bounded number of items, such that the users can get desired recommendations. We establish the upper and lower bounds of these problems, all matching, for both combined and data complexity, when selection criteria and compatibility constraints are expressed in a variety of query languages, for both item recommendation and package recommendation. To understand where the complexity comes from, we also study the impact of variable sizes of packages, compatibility constraints and selection criteria on the analyses of these problems. Our results indicate that in most cases the complexity bounds of query relaxation and adjustment recommendation are comparable to their counterparts of the basic recommendation problem for testing whether a given set of (resp. packages of) items makes top-k items (resp. packages). In other words, extending recommendation systems with the query relaxation and adjustment recommendation functionalities typically does not incur extra overhead.     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

Ions motion algorithm for solving optimization problems

This paper proposes a novel optimization algorithm inspired by the ions motion in nature. In fact, the proposed algorithm mimics the attraction and repulsion of anions and cations to perform optimization. The proposed algorithm is designed in such a way to have the least tuning parameters, low computational complexity, fast convergence, and high local optima avoidance. The performance of this algorithm is benchmarked on 10 standard test functions and compared to four well-known algorithms in the literature. The results demonstrate that the proposed algorithm is able to show very competitive results and has merits in solving challenging optimization problems.     

数字化蓄热式钢包烘烤器及自动控制系统

蓄热式燃烧技术和脉冲燃烧技术是新型的节能环保燃烧技术。数字化蓄热式钢包烘烤器控制系统利用数字化脉冲控制把这两项技术结合在一起。这大大降低了能耗，减少环境污染。本文针对数字化蓄热式钢包烘烤器，提出升温阶段采用自寻优算法，不断调整换向时间，并能记忆最优参数，保证经过几次烘烤后系统整体最优；保温阶段即采用脉冲控制的方法。     

新设备技术在催化裂化装置上的应用

文章介绍了近年来在催化裂化装置上应用的新设备、新技术,如BY型旋风分离器、BSX型旋分式三级旋风分离器、上下拱型三级旋风分离器、下拱型三级旋风分离器、SHS“自蔓延”技术、SWY外取热器、BWJ型喷嘴、自流浇注料、Actehem高耐磨衬里、弓形钢丝纤维、侧拉环锚固钉、分体可拆人孔等的结构特点及实际应用情况。     

龙潭水电站励磁装置可控硅易损原因及改进措施

通过龙潭水电站对励磁装置可控硅元件实施过电压保护改进前后实际效果的分析,介绍了一种有效的过压保护方式.     

高校摄录编播设备数字化改造探析

为了用有限的资金建设一个高标准、现代化的适合高校现代教育技术需要的数字化摄录编播系统，结合实际，详细介绍一种适合高校重大事件记录、课件制作及教学片拍摄、可以满足高校多种需求的数字化摄录编播设备的合理化配置。     

Recension des écrits sur l'impact des contacts sexuels précoces sur les hommes.

A review of the literature on the impact of sexual contacts between adults and boys reveals the existence of two principal outcomes: 1) some participants develop various disorders once in adulthood, such as behavioural problems, sexual disorders, or personality problems; 2) some participants do not present with any major disorders in the long run. These different outcomes may be associated with several moderating variables related to the sexual contacts, such as the level of coercion at the time of these contacts, the bond between the child and the adult, or the context of the sexual relation. However, the conclusions relating to the relations between early sexual contacts with adults and subsequent problems of adaptation in adulthood are difficult to determine. This is because of various methodological problems associated with relevant studies (i.e., definition of these contacts, nature of the sample, method evaluation, statistical analyses). In this article, we propose certain avenues of research that may help clarify this problem. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

协同作战能力简析

协同作战能力(CEC)是一种充分利用网络技术的新型海岸防空技术，给系统的作战能力带来了革命性的交破。本文对协同作战能力的产生、功能、组成以及未来的发展趋势作了详细的介绍，阐述了CEC系统的总体设计思想。在此基础上，将CEC系统与传统的作战系统的性能和设计思想在各方面进行了比较，交出了CEC系统各方面的优越性能。协同作战能力是现代和未来作战系统的发展方向，CEC系统的发展必将成为衡量各国国防科技现代化的重要指标。