Low-frequency wide-band hybrid energy harvester based on piezoelectric and triboelectric mechanism

Recently,hybrid energy harvester has been considered as an attractive potential approach to response the worldwide energy crisis due to the combination of advantages from different harvesting mechanism.In this paper,a novel low-frequency wide-band hybrid energy harvester based on piezoelectric and triboelectric mechanism is presented and systematically studied including structural design,fabrication process,working principle simulation and measurement.With a vibrational excitation,the polyvinylidene fluoride(PVDF) cantilevers will vibrate and impact the polydimethylsiloxane(PDMS) film on the substrate,producing a piezoelectric output as well as a triboelectric output.The structural parameters of each cantilever are optimized using finite element simulation,and the well-designed PVDF cantilevers with controllable PDMS mass not only reduce the device working frequency but also enlarge the bandwidth.Under a sweep-frequency test,three voltage peaks induced by the piezoelectric part are observed at 15,32.5 and 47.5 Hz,with the value of 320,288 and 264 mV,respectively.With the combined triboelectric part,a 20 V peak-peak voltage is generated at 15 Hz.The electrical driving ability of this hybrid energy harvester also has been demonstrated by lighting up a commercial light emitting diode(LED).     

基于ANSYS的钢模台车顶模架拓扑优化设计

以江坪河溢洪道钢模台车为例,在用ANSYS软件对顶模架初始设计方案进行有限元分析的基础上,利用ANSYS拓扑优化理论对顶模架进行了结构拓扑优化设计,并对拓扑优化后的结构设计方案进行了有限元分析。对比分析结果显示,拓扑优化后的顶模架结构刚度、强度均有一定的提高,且未增加制造难度。     

十七大以来农村改革发展理论与实践的深化

农村改革发展事关党和国家的工作大局,是全面建成小康社会的关键环节和重要领域。十七大以来,党对农村改革发展的历史和作用有了更加清晰的认识,强化了农村改革、加快发展对国民经济发展的战略性作用,明确了农业现代化的发展路径,制定了一系列农业现代化和加快推进农村改革发展的制度体系,提出了一系列重要的科学论断,进一步深化和完善了党的农村改革理论。     

Modeling deterministic echo state network with loop reservoir

Echo state network (ESN),which efficiently models nonlinear dynamic systems,has been proposed as a special form of recurrent neural network.However,most of the proposed ESNs consist of complex reservoi...     

基于流映射的负载均衡调度算法研究

网络管理者需要能够提供可扩展性、吞吐率保证及报文顺序的高性能路由器体系结构.目前基于Crossbar的集中式路由器体系结构难以实现性能和规模的可扩展,基于两级Mesh网络的负载均衡交换结构成为扩展Internet路由器容量的有效的途径.负载均衡路由器存在严重的报文乱序现象,输出端报文重定序复杂度为O(N2).文中提出一种区域均等的负载均衡交换结构,每k个连续的中间级输入端口划分为一个区域,输入端采用基于流映射的负载分配算法UFFS-k(Uniform Fine-grain Frame Spreading,k为聚合粒度,简称UFFS-k),在k个连续的外部时间槽,以细粒度的方式将同一条流的k个信元分派到固定的映射区域,通过理论证明,该调度策略可获得100%吞吐率并能够保证报文的顺序.为避免流量区域集中现象,采用双循环(dual-rotation)方式构建不同输入端口的流到区域的映射关系;为实现负载在中间级输入端口的均衡分布,每个输入端口维护全局统一视图的流量分布矩阵,UFFS-k调度算法根据流量分布矩阵调度单位帧,可以证明,对任意输出端口j,同一区域OQj队列长度相同且不同区域OQj队列长度至多差1,从而实现了100%负载均衡度.UFFS-k调度算法分布于每个输入端口独立执行,根据流到区域的映射关系及负载分布状态分派信元,模拟结果显示,当聚合粒度k=2时,UFFS-k算法在同类维序算法中表现出最优延迟性能.     

Highly discriminative statistical features for email classification

This paper reports on email classification and filtering, more specifically on spam versus ham and phishing versus spam classification, based on content features. We test the validity of several novel statistical feature extraction methods. The methods rely on dimensionality reduction in order to retain the most informative and discriminative features. We successfully test our methods under two schemas. The first one is a classic classification scenario using a 10-fold cross-validation technique for several corpora, including four ground truth standard corpora: Ling-Spam, SpamAssassin, PU1, and a subset of the TREC 2007 spam corpus, and one proprietary corpus. In the second schema, we test the anticipatory properties of our extracted features and classification models with two proprietary datasets, formed by phishing and spam emails sorted by date, and with the public TREC 2007 spam corpus. The contributions of our work are an exhaustive comparison of several feature selection and extraction methods in the frame of email classification on different benchmarking corpora, and the evidence that especially the technique of biased discriminant analysis offers better discriminative features for the classification, gives stable classification results notwithstanding the amount of features chosen, and robustly retains their discriminative value over time and data setups. These findings are especially useful in a commercial setting, where short profile rules are built based on a limited number of features for filtering emails.     

A collaborative platform for cognitive decision making in the Knowledge Society

Two key aspects of the Knowledge Society are the interconnection between the actors involved in the decision making processes and the importance of the human factor, particularly the citizen’s continuous learning and education. This paper presents a new module devoted to knowledge extraction and diffusion that has been incorporated into a previously developed decision making tool concerning the Internet and related with the multicriteria selection of a discrete number of alternatives (PRIOR-Web). Quantitative and qualitative procedures using data and text mining methods have been employed in the extraction of knowledge. Graphical visualisation tools have been incorporated in the diffusion stage of the methodological approach suggested when dealing with decision making in the Knowledge Society. The resulting collaborative platform is being used as the methodological support for the cognitive democracy known as e-cognocracy.     

Asymptotic synchronization of the Colpitts oscillator

In this paper we deal with the observer-based asymptotic synchronization problem for a class of chaotic oscillators. Some results based on a differential algebraic approach are used in order to determine the algebraic observability of unknown variables. The strategy consists of proposing a slave system (observer) which tends to follow asymptotically the master system. The methodology is tested in the real-time asymptotic synchronization of the Colpitts oscillator by means of a proportional reduced order observer (PROO) of free-model type.     

F-MPJ: scalable Java message-passing communications on parallel systems

This paper presents F-MPJ (Fast MPJ), a scalable and efficient Message-Passing in Java (MPJ) communication middleware for parallel computing. The increasing interest in Java as the programming language of the multi-core era demands scalable performance on hybrid architectures (with both shared and distributed memory spaces). However, current Java communication middleware lacks efficient communication support. F-MPJ boosts this situation by: (1) providing efficient non-blocking communication, which allows communication overlapping and thus scalable performance; (2) taking advantage of shared memory systems and high-performance networks through the use of our high-performance Java sockets implementation (named JFS, Java Fast Sockets); (3) avoiding the use of communication buffers; and (4) optimizing MPJ collective primitives. Thus, F-MPJ significantly improves the scalability of current MPJ implementations. A performance evaluation on an InfiniBand multi-core cluster has shown that F-MPJ communication primitives outperform representative MPJ libraries up to 60 times. Furthermore, the use of F-MPJ in communication-intensive MPJ codes has increased their performance up to seven times.