济阳坳陷下古生界潜山油气藏特征及成藏模式

济阳坳陷下古生界潜山具有多样性、复杂性的特点，潜山差异性的形成演化、油气成藏主控因素和控藏模式不明确，严重制约了该区潜山油气勘探。在潜山分类的基础上，综合利用系统恢复、分类对比和典型解剖等方法，揭示了济阳坳陷下古生界不同类型潜山的形成演化过程和油气成藏主控因素差异性，分类建立了油气成藏模式。研究表明，济阳坳陷下古生界主要发育高位新盖侵蚀残丘潜山、中位古盖拉张断块潜山、中位新古盖拉张剪切断块潜山、中位中古盖挤压拉张断块潜山和低位古盖拉张滑脱断块潜山5种潜山类型。不同类型潜山的形成演化和油气成藏各具特色，其中，高位新盖侵蚀残丘潜山的发育受隆升、侵蚀作用控制，油气成藏主要受控于油源和盖层条件，表现为"单向供烃、砂体-不整合岩溶体联合输导、残丘控藏"的成藏模式；中位古盖拉张断块潜山的发育受掀斜、断裂作用控制，油气成藏主要受控于储集条件，表现为"单向供烃、顺向断层输导、反向断层控藏"的成藏模式；中位新古盖拉张剪切断块潜山的发育受反转、翘倾和走滑切割作用控制，油气成藏主要受控于输导条件，表现为"多源供烃、断溶体立体输导、断裂控藏"的成藏模式；中位中古盖挤压拉张断块潜山的形成受强烈挤压、拉张滑脱作用控制，油气成藏主要受控于储集条件，表现为"多源供烃、断缝体输导、断褶控藏"的成藏模式；低位古盖拉张滑脱断块潜山的形成受强烈拉张滑脱作用控制，油气成藏主要受控于输导条件，表现为"顶部供烃、断缝体输导、断裂控藏"的成藏模式。     

论携号转网行为的私法规制

以电信用户入网协议为切入点,电信用户的携号转网行为应受到《合同法》《消费者权益保护法》等私法规范的保护与限制。该行为引起的格式条款解释、合同终止、违约责任、损失赔偿等问题,不能仅靠《电信条例》等公法规范来调整。应当积极引导广大消费者用户以私法领域相关规定为依据,转变争议解决思维,拓宽纠纷处理途径,合理选择维权手段,以保护自身合法民事权益,与行业监管部门共同推动电信行业有序发展。     

基于深度信念网络的列车故障音频诊断方法

铁路在交通运输行业有着举足轻重的地位，一旦列车发生故障将会导致严重的生命财产损失。由于列车发生故障的概率相对较低，因此难以捕获列车的故障样本。针对上述问题，提出了一种无监督学习的列车故障识别方法，通过检测列车音频信号来识别列车故障。该方法基于深度信念网络(DBN)，利用小波包分解提取检测信号的特征向量并将其作为DBN的输入，待网络充分训练后，由训练好的DBN识别当前列车的运行状况。现场监测实验结果表明，该方法能够在无监督的条件下有效识别列车故障，保障了列车的运行安全。     

社交网络中基于网络结构支撑模型的谣言传播研究

结合结构支撑理论，探究节点网络结构支持力的一些性质，提出了社交网络结构中的全网支持力和被支持力的总量一致性，并进一步提出计算节点支持力的方法。谣言作为特殊信息，在支持力不同节点之间的传播特性有所不同，借鉴随机游走模型中的PageRank计算方法，对不同节点支持力的谣言传播以及传播后的辟谣状况进行了仿真模拟，结果表明支持力不同的节点对于谣言传播和辟谣影响明显。     

基于密钥共享的分层混合认证模型

随着信息时代的迅速发展,云计算数据访问安全已经成为了用户最关心的问题。身份认证技术是确保参与者在开放的网络环境中实现安全通信的一种重要手段,如何利用身份认证技术为云环境安全保驾护航,成为学者研究的热点。文中通过公钥基础设施(Public Key Infrastructure,PKI)颁发CA证书以在不同云服务间建立信任,将多个采用身份密码体制(Identity-Based Encryption,IBE)的云联合起来；采用分层身份加密体系,引入共享密钥技术,通过选取成环结构,提出一种PKI-IBE混合认证模型方案,并对方案的安全性进行分析,从理论上证明了云环境下PKI-IBE(Public Key Infrastructure-Identity-Based Encryption)同层成环模型提供服务的可行性。同时文中设计了一种基于该模型的签密技术,通过公私密钥对实现云内认证以及跨云认证。安全性理论证明与性能分析表明,该方案在计算量稍增加的前提下,保证了足够的安全性,更加满足云环境下的用户分属不同云域的认证以及用户安全访问的需求,有效解决了云环境中数据访问的安全问题。     

多先验融合的图像显著性目标检测算法

为了更加准确地检测出图像中的显著性目标，提出了多先验融合的显著性目标检测算法。针对传统中心先验对偏离图像中心的显著性目标会出现检测失效的情况，提出在多颜色空间下求显著性目标的最小凸包交集来确定目标的大致位置，以凸包区域中心计算中心先验。同时通过融合策略将凸包区域中心先验、颜色对比先验和背景先验融合并集成到特征矩阵中。最后通过低秩矩阵恢复模型生成结果显著图。在公开数据集MSRA1000和ESSCD上的仿真实验结果表明，MPLRR能够得到清晰高亮的显著性目标视觉效果图，同时F，AUC，MAE等评价指标也比现有的许多方法有明显提升。     

Reduction of waste biosolids by RAS-ozonation: Model validation and sensitivity analysis for biosolids reduction and nitrification

Biosolids reduction model by return activated sludge ozonation was validated by simulating nitrification data compiled from our pilot-scale and the literature studies. Then, a global sensitivity analysis (GSA) was performed to identify influential and non-influential parameters for biosolids reduction efficiency, change in specific nitrification activity (SNA), and alteration to expected nitrification stability. In general, the model outputs were sensitive to operational and ozone reaction parameters, but not to biochemical parameters. For operational parameters, mainly temperature and initial solids retention time (SRT) influenced all model outputs. For biosolids reduction, increase in the degradability of the influent COD decreased the reduction efficiency. For SNA, the changes were highly dependent on the influent TKN/COD ratio. Our findings also imply that the stability of the nitrification process in ozonated systems should be enhanced at constant MLVSS for warm temperatures, but could be reduced at temperatures below 12 °C and aerated SRTs below 10 days.     

Exactly satisfying initial conditions neural network models for numerical treatment of first Painlevé equation

In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models.     

Modelling of chromatic contrast for retrieval of wallpaper images

Colour remains one of the key factors in presenting an object and, consequently, has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour‐based image retrieval. To comprehend this effect, in this article, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing the gap that most of existing colour models lack to fill by taking simultaneous colour contrast into account. Subsequently, the model is applied to the retrieval task on a collection of museum wallpapers of colour‐rich images. In comparison with current popular colour models including CIECAM02, HSI and RGB, with respect to both foreground and background colours, CAMcc appears to outperform the others with retrieved results being closer to query images. In addition, CAMcc focuses more on foreground colours, especially by maintaining the balance between both foreground and background colours, while the rest of existing models take on dominant colours that are perceived the most, usually background tones. Significantly, the contribution of the investigation lies in not only the improvement of the accuracy of colour‐based image retrieval but also the development of colour contrast model that warrants an important place in colour and computer vision theory, leading to deciphering the insight of this age‐old topic of chromatic contrast in colour science. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 361–373, 2015     

外部气体辅助注塑制品翘曲变形数值模拟

基于聚合物黏弹性理论与外部气体辅助注塑（EGAIM）的特点，构建了EGAIM气体保压阶段及脱模后自然冷却阶段制品内应力?应变的力学模型。在此基础上，采用耦合有限元法（FEM）对EGAIM平板制件的翘曲变形进行模拟计算，模拟结果与实验结果基本一致，验证了所建计算模型有效可靠。