受恶意程序传染的WSNs可生存性评估

为实现传感节点数据高可靠传输的无线传感器网络WSNs（Wireless Sensor Networks）,提出一种针对受恶意程序传染的聚簇WSNs可生存性评估方法。通过使用能预测恶意程序传染行为的博弈模型,将恶意程序传染的故意性与马尔可夫链的随机性关联,实现利用马尔可夫链中的状态转换描述恶意程序传染行为的目的。使用提出的易感节点可靠度评估指标,根据可靠性理论将聚簇WSNs看作一个“并-串-并”系统,推理得到了一个簇、一条路由直至整个WSNs的可靠度评估指标,最终得到WSNs生存期评估指标。实验分析了影响WSNs可生存性的因素,结果表明提出的方法能有效评估WSNs的可生存性,为设计高可生存的WSNs提供理论基础。     

基于恒温谐波检测双回路瓦斯浓度仪研究

针对传统气体传感器检测范围窄、易中毒、使用寿命短等缺陷,提出基于恒温谐波检测的双回路瓦斯浓度检测系统。通过ATMEGA16实现低浓度的电化学检测电路切换高浓度的红外吸收检测电路,恒温惠斯通电阻电桥检测电路可减少温度场对传感器性能影响;应用谐波检测原理消除红外光路干扰,稳定光源的输出功率,提高灵敏度。利用拉格朗日插值定理进行温度补偿,可消除温度漂移带来的瓦斯浓度二值性问题,并能在5.3%瓦斯浓度处实现高精度的瓦斯爆炸预警。实验结果表明：双回路检测仪具有高灵敏度、测量范围广、精度高等特点,可应用在突出灾害时瓦斯大量涌出检测中。     

无线传感器网络的系统化自适应建模

无线传感器网络的系统能耗制约着全网络的综合应用能力,其中节点有限的能量从根本上影响着传感器网络效能。针对无线传感器网络的全局能耗问题,提出了基于径向基函数神经网络以及状态空间表达的系统化建模方法。考虑到无线传感器网络的拓扑结构与分级关系, 采用径向基函数神经网络自适应实时规划系统。鉴于各传感器节点对数据的不同处理方式与能耗密切相关, 对全系统能耗建立系统化矩阵模型。仿真分析表明该模型可根据实际应用背景调整设置完成全局优化。     

3D-HEVC深度图像快速帧内编码方法

目的 新一代3D视频采用了多视点加深度图像的格式,其编码测试模型3D-HEVC(3D高效视频编码)为深度图像引入了一些新的编码技术,包括深度模型模式、分段直流(DC)残差编码模式和帧内跳过模式等,但是同时也显著地增加了帧内编码器的复杂度,严重制约了3D视频的实时应用,因此本文提出了一种深度图像帧内模式选择方法。方法 首先,分析在分层编码结构中,父层帧内模式和子层帧内模式的关系,并依据父层的帧内模式对子层的候选模式进行修剪;其次,通过分析粗略候选帧内模式,把当前块分为平滑块、方向块和边界块,并根据不同块进行候选帧内模式的选择。结果 与高效3D视频编码标准的测试模型相比,本文的深度图像帧内模式选择方法可以节省约44%的编码时间。本文方法有效地减少了计算率失真代价的候选帧内模式数目,从而降低了帧内编码器的复杂度。结论 该方法能在保证虚拟视点质量的前提下,有效地降低深度图像帧内编码的复杂度。     

基于决策树的大学生科研活动与毕业走向的关联研究

本科生的科研活动越来越得到教育研究者的重视,然而,研究者很少关注学生科研活动与毕业走向之间的关联问题。为了探究本科生参与科研情况对其未来发展的影响,从学生毕业走向切入,挖掘影响学生未来毕业去向的重要因素。以北京市某师范高校计算机相关专业的2009级的所有学生的科研情况与毕业走向作为数据主要来源,以Weka作为模型建立和评估的辅助工具,采用J48决策树分类,进行十折交叉验证,建立了基于学生科研活动的毕业走向预测模型,并通过对模型进行验证评估,证明了模型预测准确率良好。研究结果表明,学生参与竞赛的数量、专业、作为项目负责人的项目数量、参与教学类项目的数量对学生的未来走向有着重要影响。     

A Lyapunov‐based small‐gain approach on design of triggering conditions in event‐triggered control systems

This paper studies a Lyapunov‐based small‐gain approach on design of triggering conditions in event‐triggered control systems. The event‐triggered control closed‐loop system is formulated as a hybrid system model. Firstly, by viewing the event‐triggered control closed‐loop system as a feedback connection of two smaller hybrid subsystems, the Lyapunov‐based small‐gain theorems for hybrid systems are applied to design triggering conditions. Then, a new class of triggering condition, the safe, adjustable‐type triggering condition, is proposed to tune the parameters of triggering conditions by practical regulations. This is conducive to break the restriction of the conservation of theoretical results and improve the practicability of event‐triggered control strategy. Finally, a numerical example is given to illustrate the efficiency and the feasibility of the proposed results. Copyright © 2015 John Wiley & Sons, Ltd.     

Fuzzy decision fusion of complementary experts based on evolutionary cepstral coefficients for phoneme recognition

Optimal representation of acoustic features is an ongoing challenge in automatic speech recognition research. As an initial step toward this purpose, optimization of filterbanks for the cepstral coefficient using evolutionary optimization methods is proposed in some approaches. However, the large number of optimization parameters required by a filterbank makes it difficult to guarantee that an individual optimized filterbank can provide the best representation for phoneme classification. Moreover, in many cases, a number of potential solutions are obtained. Each solution presents discrimination between specific groups of phonemes. In other words, each filterbank has its own particular advantage. Therefore, the aggregation of the discriminative information provided by filterbanks is demanding challenging task. In this study, the optimization of a number of complementary filterbanks is considered to provide a different representation of speech signals for phoneme classification using the hidden Markov model (HMM). Fuzzy information fusion is used to aggregate the decisions provided by HMMs. Fuzzy theory can effectively handle the uncertainties of classifiers trained with different representations of speech data. In this study, the output of the HMM classifiers of each expert is fused using a fuzzy decision fusion scheme. The decision fusion employed a global and local confidence measurement to formulate the reliability of each classifier based on both the global and local context when making overall decisions. Experiments were conducted based on clean and noisy phonetic samples. The proposed method outperformed conventional Mel frequency cepstral coefficients under both conditions in terms of overall phoneme classification accuracy. The fuzzy fusion scheme was shown to be capable of the aggregation of complementary information provided by each filterbank.     

The design and test of dual/triple‐mode bandpass filter based on temporal coupled‐mode theory

In this article, the design and test of both a K‐band dual‐mode bandpass filter (BPF) pair and a K‐band triple‐mode BPF are presented based on N‐mode temporal coupled‐mode theory (CMT). The expressions of transmission and reflection responses are analytically derived. All the parameters in the expressions have clear physical meanings and are easily optimized to reach the required filter performance. Aided by eigenmode simulations, concrete structures of the three integrated BPFs are designed and optimized to approach the calculated physical parameters. After the fabrications and measurements of the three BPFs, extended upper/lower stopband with high stopband rejections are achieved, and by increasing the number of resonant modes, improved frequency selectivity and better passband flatness are obtained. The analytical analysis well predicts the simulation and measurement results, which provides an efficient way for BPF designs. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:609–622, 2016.     

Group decision making based on incomplete multiplicative and fuzzy preference relations

The main aim of this paper is to investigate the group decision making on incomplete multiplicative and fuzzy preference relations without the requirement of satisfying reciprocity property. This paper introduces a new characterization of the multiplicative consistency condition, based on which a method to estimate unknown preference values in an incomplete multiplicative preference relation is proposed. Apart from the multiplicative consistency property among three known preference values, the method proposed also takes the multiplicative consistency property among more than three values into account. In addition, two models for group decision making with incomplete multiplicative preference relations and incomplete fuzzy preference relations are presented, respectively. Some properties of the collective preference relation are further discussed. Numerical examples are provided to make a discussion and comparison with other similar methods.     

A fuzzy framework to evaluate service quality in the healthcare industry: An empirical case of public hospital service evaluation in Sicily

A novel fuzzy evaluation framework is applied in this study to evaluate service quality in the public healthcare sector. In particular, the proposed framework is based on the ServQual disconfirmation paradigm and incorporates the Analytic Hierarchy Process (AHP) method to elicit reliable estimations of service quality expectations. Moreover, degrees of uncertainty, subjectivity and vagueness on the part of stakeholders are addressed via linguistic evaluation scales parameterized by triangular fuzzy numbers. With reference to nine relevant public hospitals in the Sicilian Region (Italy), a detailed case study evaluating four core service criteria and 15 fundamental service items is conducted so as to discern dissatisfying aspects regarding the public healthcare service in the Region. Dissatisfaction reasons with the provided service are identified in the analysis as well, further demonstrating the effectiveness of the proposed approach.