Spectroscopic features and reactivity of CO adsorbed on different Au/CeO2 catalysts

An FTIR study of CO adsorption from 120 K up to room temperature on a series of Au–ceria samples is presented. Samples with low gold content (0.7 and 0.6 at%) were prepared by urea gelation/co-precipitation and by cyanide leaching of the high-gold content (5.8 at%) material prepared by deposition–precipitation on La-doped CeO₂. The samples were subjected to different pretreatments to collect information on the surface composition under working conditions. An absorption band at 2130–2140 cm⁻¹, not reversible on outgassing and more resistant to oxidation than the usual carbonyl band on Au⁰ sites, was present due to CO adsorbed on cationic gold clusters. This highly stable species is relevant for hydrogen gas upgrade by removing CO from reformate-type gases at low temperatures. In addition, a broad absorption band in the 2000–2100 cm⁻¹ range was observed after reduction in hydrogen, due to structural and electronic changes of gold. Interestingly, the reduced gold species in ceria can be reoxidized at mild conditions. Light-off of the CO oxidation reaction took place below room temperature on the metallic gold-containing ceria but was delayed until 310 K on the ionic gold-containing sample. TPR and XPS analysis of the fresh and used catalysts corroborated the stability of ionic gold in ceria up to 393 K in the reaction gas mixture.     

Synthesizing English emphatic speech for multimodal corrective feedback in computer-aided pronunciation training

Emphasis plays an important role in expressive speech synthesis in highlighting the focus of an utterance to draw the attention of the listener. We present a hidden Markov model (HMM)-based emphatic speech synthesis model. The ultimate objective is to synthesize corrective feedback in a computer-aided pronunciation training (CAPT) system. We first analyze contrastive (neutral versus emphatic) speech recording. The changes of the acoustic features of emphasis at different prosody locations and the local prominences of emphasis are analyzed. Based on the analysis, we develop a perturbation model that predicts the changes of the acoustic features from neutral to emphatic speech with high accuracy. Further based on the perturbation model we develop an HMM-based emphatic speech synthesis model. Different from the previous work, the HMM model is trained with neutral corpus, but the context features and additional acoustic-feature-related features are used during the growing of the decision tree. Then the output of the perturbation model can be used to supervise the HMM model to synthesize emphatic speeches instead of applying the perturbation model at the backend of a neutral speech synthesis model directly. In this way, the demand of emphasis corpus is reduced and the speech quality decreased by speech modification algorithm is avoided. The experiments indicate that the proposed emphatic speech synthesis model improves the emphasis quality of synthesized speech while keeping a high degree of the naturalness.     

Terrain‐inclination‐based Three‐dimensional Localization for Mobile Robots in Outdoor Environments

A new terrain‐inclination‐based localization technique is proposed in this paper to enable a robot to identify its three‐dimensional location relative to measurable terrain inclinations. Given a topographical map and a planned path, a robot‐terrain‐inclination model (RTI model) is extracted along the path on the terrain upon which the robot is operating. A particle filter is then used to fuse the measurement data with the robot motion based on the extracted RTI model for either a three‐wheeled or a four‐wheeled mobile robot. Experiments were carried out in four outdoor scenarios: one short path with different initial conditions and map resolution, another short path with different surface roughness and sensor accuracy, and two long paths with different types of rigid terrains and multiple loops. Experimental results show that the proposed method could achieve good localization performance on inclined outdoor terrains.     

Low-sintering ceramic materials based on Bi2O3–ZnO–Nb2O5 compounds

In this work, sintering behaviour of Bi₂O₃–ZnO–Nb₂O₅ compounds was investigated in order to develop LTCC materials with suitable microwave properties. Structure, dielectric properties and sintering were studied for ceramic dielectrics based on the system: Bi₂ZnNb₂O₉ with the pyrochlore structure and ZnNb₂O₆ with a columbite one. The work was carried out over a wide range of initial components concentration. Ceramic samples of these materials were prepared by the mixed oxide technique. The effect of adding glass to the materials have been discussed. The sintering behaviour, dielectric permittivity, quality factor and crystal structures have been characterized for ceramic samples depending on compositions. Low-temperature co-firable ceramic material with ɛ ∼ 30, τ_ɛ = 0 and Q × f = 3500 GHz based on the above system was synthesized.     

大规模认知无线电网络的时延分析

时延作为无线网络的最基本的性能之一,对网络信息分发、路由协议设计、节点部署等都具有重要意义。与传统的无线网络不同,认知无线电网络的频谱资源具有动态变化性,该特性会对网络时延产生极大的影响。因此,如何对动态频谱环境下的大规模认知无线电网络进行时延分析,是一项很具挑战性的课题。为此,首先对动态频谱环境进行建模,将认知用户的频谱接入过程建模为一个连续时间的马尔可夫链,并建立认知用户的生存函数来量化授权用户活动以及信道数量对频谱环境的影响;其次,将上述模型与首次通过渗流理论结合起来,研究了大规模认知无线电网络时延的伸缩规律,并获取了更为精确的时延与距离比的上限值。理论分析及仿真结果表明,动态频谱环境与密度一样会对时延产生极大影响。研究结论对认知无线电网络的设计具有重要的指导意义。     

基于节点分割的社交网络属性隐私保护

现有研究表明,社交网络中用户的社交结构信息和非敏感属性信息均会增加用户隐私属性泄露的风险.针对当前社交网络隐私属性匿名算法中存在的缺乏合理模型、属性分布特征扰动大、忽视社交结构和非敏感属性对敏感属性分布的影响等弱点,提出一种基于节点分割的隐私属性匿名算法.该算法通过分割节点的属性连接和社交连接,提高了节点的匿名性,降低了用户隐私属性泄露的风险.此外,量化了社交结构信息对属性分布的影响,根据属性相关程度进行节点的属性分割,能够很好地保持属性分布特征,保证数据可用性.实验结果表明,该算法能够在保证数据可用性的同时,有效抵抗隐私属性泄露.     

医疗大数据特征挖掘及重大突发疾病早期预警

通过运用新兴的尖端云计算技术,设计研发了健康云平台。采用分布式云存储技术存储大规模的异构多模态生理信号数据,将数据挖掘模型（L1-逻辑斯蒂）整合至MapReduce框架中,快速挖掘用户的健康信息以及重大疾病高风险因子,让用户能实时地了解自己的身体状况,同时对用户的异常状况给出预警信息,并通知其前往医院就医,实现了对重大突发疾病的早期预警。     

Electrochemical insertion of lithium into a doped diamond film grown on carbon felt substrates

This paper summarizes the preliminary results obtained from lithium electrochemical intercalation into boron-doped diamond films grown on carbon felt (BDD/CF electrode). BDD films have been grown by Hot Filaments Chemical Vapor Deposition (HFCVD) and have been characterized by Scanning Electron Microscopy (SEM) and Raman Scattering spectroscopy. BDD/CF composite electrodes, which contain a diamond layer, lead to higher conductivity and smaller grain sizes. In turn, they are richer in boundary or sp² sites, and present a reversible specific capacity that is much larger than that of the substrate alone, indicating that the diamond layer effectively participates in lithium storage. Diamond layers displaying boron doping levels of 10¹⁹ and 10²¹ part cm^− 3 provide a specific capacity of 160 and 370 mA h g^− 1, respectively, which is associated with lithium storage.     

一种鲁棒的可视外壳生成算法*

针对各种传统可视外壳生成算法中数据冗余、精确度低、健壮性不足等问题, 提出了一种新的可视外壳生成算法,即采用加权线段求交、线段集合中心线性过滤、多边形边界检测等方法重建物体模型。与传统方法相比,本算法能够更稳定地计算线段交集,表面边界提取更加准确,重建结果精确逼近真实物体。实验表明, 通过该算法计算的物体可视外壳能够更好地逼近真实模型,精度高。     

彩钢岩棉夹芯屋面板、墙面板节点性能研究

为了掌握彩钢岩棉夹芯屋面板、墙面板与檩条的螺钉连接节点抗拉破坏机理,采用理论分析、试验验证及有限元模拟相结合的方法研究了不同钢板厚度及芯材厚度时节点破坏情况.分析结果表明:屋面板节点连接破坏是由于钢板局部屈曲引起的,墙面板则是钢板被冲剪破坏造成的,同时,结合对有限元模拟结果的回归,提出了节点承载力设计公式,可为以后节点设计提供参考.增加岩棉刚度及其与侧向钢板的粘结,或增加钢板厚度对提高屋面板节点极限承载力起着重要作用.