A New View on Fuzzy Hypermodules

We describe the relationship between the fuzzy sets and the algebraic hyperstructures. In fact, this paper is a continuation of the ideas presented by Davvaz in （Fuzzy Sets Syst., 117： 477- 484, 2001） and Bhakat and Das in （Fuzzy Sets Syst., 80： 359-368, 1996）. The concept of the quasicoincidence of a fuzzy interval value with an interval-valued fuzzy set is introduced and this is a natural generalization of the quasi-coincidence of a fuzzy point in fuzzy sets. By using this new idea, the concept of interval-valued （α,β）-fuzzy sub-hypermodules of a hypermodule is defined. This newly defined interval-valued （α,β）-fuzzy sub-hypermodule is a We shall study such fuzzy sub-hypermodules and sub-hypermodules of a hypermodule. generalization of the usual fuzzy sub-hypermodule. consider the implication-based interval-valued fuzzy     

Performance Analysis for Mobile Ad Hoc Network in Random Graph Models with Spatial Reuse

In this paper,we present a random graph model with spatial reuse for a mobile ad hoc network(MANET) based on the dynamic source routing protocol.Many important performance parameters of theMANET are obtained,such as the average flooding distance (AFD),the probability generating function of theflooding distance,and the probability of a flooding route to be symmetric.Compared with the random graphmodel without spatial reuse,this model is much more effective because it has a smaller value of AFD and alarger probability for finding a symmetric valid route.     

Learning Theory Estimates via Integral Operators and Their Approximations

The regression problem in learning theory is investigated with least square Tikhonov regularization schemes in reproducing kernel Hilbert spaces (RKHS). We follow our previous work and apply the sampling operator to the error analysis in both the RKHS norm and the L² norm. The tool for estimating the sample error is a Bennet inequality for random variables with values in Hilbert spaces. By taking the Hilbert space to be the one consisting of Hilbert-Schmidt operators in the RKHS, we improve the error bounds in the L² metric, motivated by an idea of Caponnetto and de Vito. The error bounds we derive in the RKHS norm, together with a Tsybakov function we discuss here, yield interesting applications to the error analysis of the (binary) classification problem, since the RKHS metric controls the one for the uniform convergence.     

OR and the challenge to improve the NHS: modelling for insight and improvement in in-patient flows

This paper considers efforts to improve in-patient flows, a particularly urgent issue in the National Health Service (NHS). The context is described and related to reasons why OR has been making relatively little contribution. The paper argues that large complex models may often be unnecessary and even get in the way of providing clear insight and guidance for problem owners. The importance of understanding the generic working of systems to lead to improvement, and the limitations of simply describing them, is stressed. It is demonstrated that some very simple models can be of significant practical value in understanding and managing complex systems, changing mindsets and driving collection and use of operationally valuable data. Recommendations for more effective engagement with the NHS are offered.     

Resource Search in Unstructured Peer-to-Peer System Based on Multiple-Tree Overlay Structure

We propose a multiple-tree overlay structure for resource discovery in unstructured P2P systems. Peers that have similar interests or hold similar type of resources will be grouped into a tree-like cluster. We exploit the heterogeneity of peers in each cluster by connecting peers with more capacities closer to the root of the tree. The capacity of a peer can be defined in different ways （e.g. higher network bandwidth, larger disk space, more data items of a certain type etc.） according to different needs of users or applications.     

Functional magnetic resonance imaging of amphetamine craving

The aim of this study is to identify the brain activity associated with amphetamine craving for understanding the neurobiology of addiction by watching pictures of happy, sad or amphetamine. Brain activity was measured in 12 amphetamine addicts and 12 healthy subjects by fMRI while the subjects watched pictures designed to elicit happy feelings, sad feelings, or the desire to use amphetamine. The result demonstrated that amphetamine cues led to abnormally high cingulate and low frontal lobe activation in amphetamine addicts, who showed abnormalities in affect-related brain activation.     

The Response of Debris-Flow Events to Solar Proton Flares （Ⅰ）

By analyzing the observation data from Dongchuan Debris Flow Observation and Research Station and historical data from year 1965 to 1990 gotten from National Astronomical Ob-servatories/Yunnan Observatory,the responding of debris flow in Jiangjia Ravine to Solar Proton Flare is studied. The following conclusion can be drawn. Solar Proton Flare,as one of most im-portant astronomical factors,affects the activity of debris flow in Yunnan. Generally,from 1965 to1990,the more active Solar Pro-ton Flare is,the greater the probability of high frequency and large runoff of debris flow is. On the contrary,the less active Solar Pro-ton Flare is,the greater the probability of low frequency,small runoff,and low sediment transport of debris flow is.     

一种信息审计系统中的多关键字匹配算法

针对审计系统中搜索大量审计数据的需要,设计了一种基于哈希表机制的多关键字匹配算法.该算法把关键字集合储存到哈希表中,并为关键字集合建立了两个过滤表和一个关键字长度类型表.在查找过程中,对未经过滤表验证的字符串不再进行匹配查找,同时,关键字长度类型表的使用减少了循环的次数.测试结果表明,该算法在速度和精度上都优于BM和mgrep算法.