Inference and learning in hybrid probabilistic network

This paper proposed a novel hybrid probabilistic network, which is a good tradeoff between the model complexity and learnability in practice. It relaxes the conditional independence assumptions of Naive Bayes while still permitting efficient inference and learning. Experimental studies on a set of natural domains prove its clear advantages with respect to the generalization ability.     

Methodological Challenges in Union Commitment Studies.

Methodological problems in studies of union commitment were identified and illustrated with data from 4,641 members and 479 stewards in 297 local teachers' unions. Using a 20-item union commitment scale, results confirmed the existence of 3 substantive factors and 1 method factor at the individual level of analysis: loyalty to the union, responsibility to the union, willingness to work for the union, and a factor of negatively worded items. Tests of measurement invariance showed that the scale captured commitment for rank-and-file members but not for union stewards. The authors also found partial measurement invariance between long-time and newer members and full measurement invariance between men and women. Finally, the authors found that violation of the statistical assumption of independence reduced model fit when individual commitment scores were analyzed without attention to the hierarchical nature of the data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The social parameter of "learned" helplessness: Its recognition and implications.

Reexamines experiments on learned helplessness that have been interpreted previously as involving a solitary person experiencing uncontrollable and inescapable events. It is suggested that the belief that the outcomes are uncontrollable precludes the possibility that control of the outcomes can be transferred to the experimental Ss. An alternative interpretation is that the outcomes in learned helplessness experiments, rather than being uncontrollable, are controlled by the experimenter. Helplessness could be reduced by transferring this control to Ss, giving them control over their contingencies. This analysis has implications regarding both the accuracy of depressed people's perceptions and the desirability of making depressed people perceive an internal locus of control. It is further suggested that depressed people should have more control over their contingencies. (34 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

P2P网络中基于身份的消息链接密钥隔离加密

针对P2P网络中存在密钥泄露和大量数据加密传输困难的问题,采用密钥隔离机制和消息分组链接加密的方法,提出一种具有消息链接性的基于身份密钥隔离加密方案。在随机预言机模型下给出形式化证明,该方案在双线性Deffie-Hellman假设成立的条件下,满足适应性选择消息攻击不可区分性,且该方案具有非限定时间周期以及随机存取密钥更新的性质。性能分析结果表明,该方案的密文长度仅为基本密钥隔离加密方案的一半,适用于P2P网络中传输大量的加密数据。     

无线传感器网络中一次性数字签名算法设计

一次性数字签名算法是构造密码协议的基础算法,可用于认证无线传感器网络(WSN)中传输数据的真实性和完整性。针对WSN的应用需求,给出一种高效的一次性数字签名算法。与现有一次性签名算法相比,该算法生成签名简单快捷,只需执行一次模指数乘法运算;签名长度短,只需传输一个群元素;适用范围广,能根据待签名消息的长度自动适配对应的公钥参数,该特性非常适合WSN中数据传输量较小的应用;同时该算法还能在标准模型下得到形式化的安全证明,其抗伪造攻击安全性可归约为双线性映射群中计算的Diffie-Hellman数学难题。     

论军民一体化装备维修保障体制设计的前提假设

前提假设反映了军民一体化装备维修保障体制建立的理念与核心价值观,是体制设计和任务建立的理论基础。军民一体化装备维修保障体制设计的前提假设包括：维修主体的人性有善有恶,维修行为主要体现为经济人模式,军方具有有限维修能力,装备维修保障系统是开放的多主体复杂适应系统。最后,对加强我军军民一体化装备维修保障体制建设提出了几点启示。     

Static solution on four-region spherial cavity expansion model in a pressure sensitive medium

Spherical cavity expansion model is often used to study the mechanic characteristics of pressure sensitive mediums. The most important one we do in the paper is that we construct a four-region model with σθ≠0 in damage region,which is different from what Satapathy did before and is more reasonable. By adopting this model,different constitutive equations were constructed by different method-elastic mechanics in elastic region,damage mechanics and fracture mechanics in damage region,and macro-micro mechanics theory in plastic region. Then using Durban's self-similarity assumption,the control differential equations with boundary conditions were established,and the static numerical solution of stress field and displacement field in the three different regions of elastic,damage and plastic area were discussed respectively. Results showed that this four-region model can describe precisely the mechanic characteristics of pressure sensitive mediums under initial pressure.     

可信网络匿名连接方案

在开放式网络连接环境中,可信网络终端在进行身份证明时不希望暴露自己的身份,本文提出了一种基于环签名的可信网络连接客户端匿名认证方案,引入环管理员机制以保证环成员都是合法的可信网络连接客户端,本方案的安全性基于CDH假设和强单向函数,且参数较短,易于实现.     

基于暗原色及入射光假设的单幅图像去雾

目的 雾是一种常见的天气状况,针对雾能使图像中的景物对比度降低、表面颜色退化的问题,提出一种基于入射光假设的单幅图像去雾方法。方法 首先利用全局暗原色进行初步去雾,从而使图像透射率处于[0,1]范围内;然后利用雾天光照均匀的特点以及Retinex的照度估计原理进行透射图的估计;最后利用透射图以及初步去雾图像得到复原图像。结果 与He算法、Fattal算法的对比实验结果显示,该算法获得的复原图像细节清晰,颜色自然。与引导滤波优化后的He去雾算法相比,本文算法速度提高了93%。结论 大量对比实验结果表明,本文算法能够显著恢复雾天降质图像,对于薄雾和浓雾同样有效,具有广泛的适用性,且算法原理简单。此外,本文算法也同样适用于灰度图。     

Global structure constrained local shape prior estimation for medical image segmentation

Organ shape plays an important role in clinical diagnosis, surgical planning and treatment evaluation. Shape modeling is a critical factor affecting the performance of deformable model based segmentation methods for organ shape extraction. In most existing works, shape modeling is completed in the original shape space, with the presence of outliers. In addition, the specificity of the patient was not taken into account. This paper proposes a novel target-oriented shape prior model to deal with these two problems in a unified framework. The proposed method measures the intrinsic similarity between the target shape and the training shapes on an embedded manifold by manifold learning techniques. With this approach, shapes in the training set can be selected according to their intrinsic similarity to the target image. With more accurate shape guidance, an optimized search is performed by a deformable model to minimize an energy functional for image segmentation, which is efficiently achieved by using dynamic programming. Our method has been validated on 2D prostate localization and 3D prostate segmentation in MRI scans. Compared to other existing methods, our proposed method exhibits better performance in both studies.