Synthesis of quantum size ZnO crystals and their gas sensing properties for NO2

Quantum size ZnO crystals have been synthesized successfully by a room temperature sol-gel process. Oleic acid (OA) has been used as capping agent to control the particle size of ZnO. The crystal structure and size of the ZnO are characterized by the X-ray diffraction (XRD) and transmission electron microscope (TEM). The XRD results show the as-synthesized ZnO has hexagonal wurtzite structure and the average crystallite size is 5.7 nm which is little less than TEM result. It is testified by photoluminescence (PL) and Raman spectra that the quantum size ZnO keeps the crystal structure of the bulk ZnO and possesses more surface defects. The quantum size ZnO has the highest response of 280 to NO₂ and the highest selectivity of 31 and 49 corresponding to CO and CH₄ at operating temperature of 290 °C. The effect of calcination temperatures on sensing property and transient response of the ZnO sensor are also investigated.     

A property-based attestation protocol for TCM

This paper presents a property attestation protocol for the security chip TCM (trusted cryptographic module) via analyzing the problems of the current property attestation, which is built on the property attestation model with the online trust third party. In the protocol the prover utilizes the zero-knowledge proof by the attribute certificates, configuration commitment and TCM signature, and attests its configuration and status which are compliant with the declarative security property. The protocol is ch...     

Local and Global Interactions in an Evolutionary Resource Game

Conditions for the emergence of cooperation in a spatial common-pool resource game are studied. This combines in a unique way local and global interactions. A fixed number of harvesters are located on a spatial grid. Harvesters choose among three strategies: defection, cooperation, and enforcement. Individual payoffs are affected by both global factors, namely, aggregate harvest and resource stock level, and local factors, such as the imposition of sanctions on neighbors by enforcers. The evolution of strategies in the population is driven by social learning through imitation, based on local interaction or locally available information. Numerous types of equilibria exist in these settings. An important new finding is that clusters of cooperators and enforcers can survive among large groups of defectors. We discuss how the results contrast with the non-spatial, but otherwise similar, game of Sethi and Somanathan (American Economic Review 86(4):766–789, 1996).      

基于Bark域噪声估计及掩蔽效应的语音增强

针对非平稳环境下噪声估计和语音增强性能降低的特点,提出一种基于Bark域的快速自适应噪声谱估计算法。它基于听觉模型,将带噪信号变换到Bark域,并在Bark域内实现基于人耳掩蔽的语音增强。仿真实验表明该算法能充分利用Bark带内频带间的相关性,跟踪快变的背景噪声,提高语音增强性能,减少运算量和复杂度。     

冲击作用下碳纤维混凝土的力敏性试验研究

碳纤维混凝土(CFC)具有良好的力敏特性,能制成传感器用于混凝土结构的状态监测.利用钢球自由落体撞击圆柱形试样,进行了老化前后和不同撞击高度的试验,并分析了各因素对试样力敏性的影响.试验结果表明:试样的电阻变化对冲击作用响应快;老化前的试样在承载较小时,试样处于弹性区,电阻随压力增大而减小,承载较大时,试样进入弹塑性区,电阻随压力增大而增大;老化后的试样,承载即进入弹塑性区.     

变压器漏磁热损的光纤Bragg光栅检测与温升特性分析

变压器的漏磁场强度随着变压器容量的增大而增大,漏磁场强度越大在变压器各结构中引起的漏磁损耗越大,导致变压器运行效率低下,进而影响变压器的正常运行。对35 kV变压器进行试验,将漏磁产生最大处的温度与油箱产生顶端处的温度进行了对比,试验得出当开风机时该处与油箱顶端处的最高温度差为8.7℃、当负荷降至1倍功率时温差为2.9℃,它们的实时温度曲线图与变压器的运行一致,产生了局部温升的现象。通过光纤Bragg光栅（ FBG）检测温度的变化反映变压器漏磁的情况,从而实现了对变压器漏磁的实时在线监测。     

UWSNs中基于压缩感知的移动数据收集方案

由于水下无线传感器网络(UWSNs)工作环境的特殊性,降低节点能耗和保证数据收集的实时性是至关重要的问题.提出一种基于压缩感知(CS)的移动数据收集方案.以DEBUC协议和CS理论为基础,簇内节点依据设计的稀疏测量矩阵决定是否参与压缩采样,并将获得的测量值传输至簇头.通过AUV的移动来收集各个簇头上的数据到数据中心,该问题被建模为带有邻域的旅行商问题,并提出了近似算法进行求解.在数据中心处利用CS重构算法进行数据重构.仿真实验结果表明:相比于已有的水下移动数据收集算法,该方案在保证数据收集可靠性的同时,降低了数据收集延时,延长了网络寿命.     

基于用户签到和地理属性的个性化位置推荐算法研究

针对基于LBSNs (Location-based Social Networks)的位置推荐算法考虑因素单一且不能有效解决用户位于不同城市的位置推荐的问题,综合考虑潜在的社交影响、内容匹配影响和地理属性影响等因素,提出了基于用户签到和地理属性的个性化位置推荐算法SCL (Social-Content-Location)。该算法在协同过滤的基础上,引入了用户兴趣特征比较,改进了用户的相似度计算;同时,在分析位置的内容信息时,融入用户评论,缓解了位置标签的短文本特性对LDA (Latent Dirichlet Allocation)主题提取的影响,提高了用户兴趣和城市偏好主题提取的准确率。实验结果表明,SCL算法在本地城市召回率上较协同过滤算法U提高近65%,较LCA-LDA算法提高近 30%;在异地城市召回率上,高于LCA-LDA算法近26%。这表明SCL算法在不同城市下的位置推荐具有一定的可行性。     

WSN中基于压缩感知的高能效数据收集方案

可靠高效的数据收集是无线传感器网络（Wireless sensor networks,WSN）应用中的关键问题.然而,由于无线通信链路的高失效率、节点资源受限以及环境恶劣等原因,网络容易发生丢包问题,使得现有的数据收集方法无法同时满足高精度和低能耗的要求.为此,本文提出了一种基于压缩感知的高能效数据收集方案.该方案主要分为节点上的数据处理和数据收集路径优化两个步骤.首先设计了基于指数核函数的稀疏矩阵来对感知数据进行稀疏化处理,然后综合考虑了数据的传输能耗和可靠性等因素,采用分块矩阵的思路,将单位矩阵和准循环低密度奇偶校验（Low density parity check,LDPC）码的校验矩阵相结合构造了测量矩阵,并证明了它与稀疏矩阵之间满足限制等距性质（Restricted isometry property,RIP）.最后,将数据收集路径优化问题建模为哈密尔顿回路问题,并提出了基于树分解的路径优化算法进行求解.仿真结果表明,在网络存在丢包的情况下,本文方案仍然能够保证数据收集的高精确度,相比于其他数据收集方案而言,本文方案在数据重构误差和能耗方面的性能更优.