混合匹配规则的否定选择算法

针对目前基于免疫的检测器生成算法中,匹配规则单一造成的检测器质量低下的问题,提出一种基于混合匹配规则的否定选择算法,采用海明距离整体匹配的各段内R连续比特匹配的否定选择算法,即混合匹配否定选择算法,对算法的性能进行了分析．实验结果表明,该算法能够高效地产生所需要的检测器,提高了检测率,且降低了误报率．     

基于 ROS 改进算法的无线传感器网络耗能研究

成对广播同步（PBS）是无线传感器网络同步研究的重要协议。无线传感器节点具有体积受限、通信能力有限、存储空间较低、能量有限等特点,对传统的时钟同步协议改进是非常有必要的。因此,研究无线传感器网络的时钟同步算法将具有重要的意义。文章建立在仅接收端（ROS）同步基础上实现范围广阔的网络同步,并且能够在无线传感器网络节点的能耗方向有着不可忽视的作用。通过对单簇网络同步的研究,提出多簇网络同步并对多簇网络同步在无线传感器网络同步中全网成对选择算法（NPA）和基于组的成对选择算法（GPA）做出研究,并且做出了仿真对比。结果显示：在传感器节点数目较少的情况下,NPA 算法与 GPA算法处理消息包数目的性能几乎相同;在网络中传感器节点数目比较多的情况下,GPA 算法明显优于 NPA 算法,信息处理过程中大大减少了消息包数目。最后,对广播同步技术在应用中所出现的问题,提出了基于此算法的新的研究方向。     

阻火器的选用

阻火器的选用是石油化工厂、石油和天然气工厂、有可燃性气体的工厂生产安全保护和工程设计中常遇到并需解决的问题，本文对阻火器产品的选用步骤提出了个人的一些理解意见。     

基于遗传二进制粒子群混合算法的测试点决策研究

测试点选择是测试性分析和设计的前提。通过对测试问题的分析,建立了数学模型和构造了衡量测试集优劣程度的启发式函数,提出了一种遗传-二进制粒子群混合算法求解满足测试性指标要求的最小完备子集。应用实例表明,该算法能够有效的克服单一算法陷入局部最优和早熟收敛等不足,提高了搜索效率,能够有效快速的获得全局最优解。     

乳胶涂料中填料粒径测定与分散剂的选择

介绍了重力沉降法和容量沉降法两种测定乳胶涂料中填料粒径的方法。通过比较粉体粒径结果显示：沉降法比激光法更形象直观，更能代表体系粒径真实情况。以滑石粉、重钙、轻钙粉体为基准，采用不同用量、不同类型的分散剂的容量沉降法进行比较得出：用容量沉降法能定量地对分散剂性能做出评价。     

Feature selection on probabilistic symbolic objects

In data analysis tasks, we are often confronted to very high dimensional data. Based on the purpose of a data analysis study, feature selection will find and select the relevant subset of features from the original features. Many feature selection algorithms have been proposed in classical data analysis, but very few in symbolic data analysis （SDA） which is an extension of the classical data analysis, since it uses rich objects instead to simple matrices. A symbolic object, compared to the data used in classical data analysis can describe not only individuals, but also most of the time a cluster of individuals. In this paper we present an unsupervised feature selection algorithm on probabilistic symbolic objects （PSOs）, with the purpose of discrimination. A PSO is a symbolic object that describes a cluster of individuals by modal variables using relative frequency distribution associated with each value. This paper presents new dissimilarity measures between PSOs, which are used as feature selection criteria, and explains how to reduce the complexity of the algorithm by using the discrimination matrix.     

Relay selection with feedback beamforming information through designed sector sweep report frame for mmWave WPANs

This paper proposes a novel relay selection strategy based on the feedback beamforming （BF） information through designed sector sweep （SSW） report frame for millimeter-wave （mmWave） wireless personal networks （WPANs）. First, an SSW report frame compatible with IEEE 802.11ad standard is designed. Second, an approach collecting instantaneous channel state information （CSI） overheard during BF is devised. Third, with the aim of minimizing the outage probability and maximizing the overall network throughput capacity, the optimal relay selection issue for non-line-of-sight （NLoS） links is formulated as a bipartite graph, and Kuhn Munkres （KM） algorithm is provided to resolve it. Both theoretical analysis and simulation results show, with CSI considering NLoS conditions and selected relays according to the overall network throughput capacity maximization principle, the improvements achieved over opportunistic relay selection strategy in terms of overall network throughput capacity and outage probability with minimal modifications to IEEE 802.1lad.     

Joint optimal sensing time and power allocation for multi-channel cognitive radio networks considering sensing-channel selection

In this paper,we consider a multi-channel cognitive radio network(CRN)where each secondary user(SU)can only choose to sense a subset of channels.We formulate a joint optimization problem of sensingchannel selection,sensing time and power allocation under the constraints of average transmit power budget and average interference power budget,which maximizes the CRN’s total throughput.We propose a greedy algorithm to solve the joint optimization problem,which has much less computational complexity.Moreover,it is shown that the search space of the greedy algorithm can be further pruned.Finally,numerical results demonstrate that the greedy algorithm has comparable performance to the exhaustive search algorithm.     

Electroantennographic and behavioral responses of the sphinx moth Manduca sexta to host plant headspace volatiles

Coupled gas chromatography with electroantennographic detection (GC-EAD) using antennae of adult female Manduca sexta was employed to screen for olfactory stimulants present in headspace collections from four species of larval host plants belonging to two families: Solanaceae—Lycopersicon esculentum (tomato), Capiscum annuum (bell pepper), and Datura wrightii; and Martyniaceae—Proboscidea parviflora. Headspace volatiles were collected from undamaged foliage of potted, living plants. GC–EAD revealed 23 EAD-active compounds, of which 15 were identified by GC-mass spectrometry. Identified compounds included aliphatic, aromatic, and terpenoid compounds bearing a range of functional groups. Nine EAD-active compounds were common to all four host plant species: (Z)-3-hexenyl acetate, nonanal, decanal, phenylacetaldehyde, methyl salicylate, benzyl alcohol, geranyl acetone, (E)-nerolidol, and one unidentified compound. Behavioral responses of female moths to an eight-component synthetic blend of selected tomato headspace volatiles were tested in a laboratory wind tunnel. Females were attracted to the blend. A comparison of responses from antennae of males and females to bell pepper headspace volatiles revealed that males responded to the same suite of volatiles as females, except for (Z)-3-hexenyl benzoate. EAD responses of males also were lower for (Z)- and (E)-nerolidol and one unidentified compound. Electroantennogram EAG dose–response curves for the 15 identified EAD-active volatiles were recorded. At the higher test doses (10–100 g), female antennae yielded larger EAG responses to terpenoids and to aliphatic and aromatic esters. Male antennae did respond to the higher doses of (Z)-3-hexenyl benzoate, indicating that they can detect this compound. On the basis of ubiquity of the EAD-active volatiles identified to date in host plant headspace collections, we suggest that M. sexta uses a suite of volatiles to locate and identify appropriate host plants.     

移动群智感知中基于联邦学习的参与者选择机制

移动群智感知的发展使得一些任务收集的数据量过大,需要在不接收参与者原始数据的情况下评估数据质量并进行参与者选择。针对这一问题,提出一种基于联邦学习的移动群智感知参与者选择机制。考虑参与者智能终端资源水平、所处交互状态构建参与者智能终端资源评价机制,提出基于线性回归和长短期记忆网络的智能终端资源预测模型。通过预训练测试模型,评估参与者提供的数据质量,结合历史任务完成情况建立参与者信誉评价模型,实现对参与者的动态评价选择。仿真实验结果表明,所提的参与者选择机制在任务完成质量、能量消耗、通信轮数及任务完成时间等多方面体现出较好的性能。