Space-Confined Atomic Clusters Catalyze Superassembly of Silicon Nanodots within Carbon Frameworks for Use in Lithium-Ion Batteries

Incorporating nanoscale Si into a carbon matrix with high dispersity is desirable for the preparation of lithium-ion batteries (LIBs) but remains challenging. A space-confined catalytic strategy is proposed for direct superassembly of Si nanodots within a carbon (Si NDs⊂C) framework by copyrolysis of triphenyltin hydride (TPT) and diphenylsilane (DPS), where Sn atomic clusters created from TPT pyrolysis serve as the catalyst for DPS pyrolysis and Si catalytic growth. The use of Sn atomic cluster catalysts alters the reaction pathway to avoid SiC generation and enable formation of Si NDs with reduced dimensions. A typical Si NDs⊂C framework demonstrates a remarkable comprehensive performance comparable to other Si-based high-performance half LIBs, and higher energy densities compared to commercial full LIBs, as a consequence of the high dispersity of Si NDs with low lithiation stress. Supported by mechanic simulations, this study paves the way for construction of Si/C composites suitable for applications in future energy technologies.     

Speech emotion recognition based on statistical pitch model

A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech. The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85% if the traditional parameters are utilized.     

信用担保风险的模糊综合评审研究

信用担保机构是连接银行和企业的桥梁，对于改善企业融资环境和拓展银行业务具有重要意义，信用担保风险的评审是担保机构能否生存及有效运行的关键。信用风险的评审机制主观性强，对担保项目进行客观，公正的评审比较困难。本采用模糊数学中的综合判别方法，全面考虑风险评审所涵盖的各种风险指标及其重要度，建立了定性分析与定量分析方法相结合的信用担保风险综合评审模型，为担保机构提供了一种相对科学、客观的评审方法。     

ZnS∶Zn,Pb蓝粉在低压阴极射线激发下的应用

通过对ZnS∶Zn,Pb蓝色荧光粉进行表面包覆SiO2以改善其稳定性;In2O3材料的适量混合,提高了荧光粉的导电性,降低了它的起辉电压。采用沉淀法制备荧光屏,考察了阳极电压和阳极电流对亮度以及衰减过程的影响,实验结果表明ZnS∶Zn,Pb的性能优于ZnS∶Ag,Cl和ZnS∶Zn,可适用于FED等低压显示器。     

含氟碳菁染料聚集行为的研究

本文对五种不同结构的含氟碳菁染料的甲醇溶液及吸附在碘溴化银T 颗粒表面的聚集行为进行了研究 ,测定了照相性能 ,计算了增感倍率。Dye1 ,Dye2 ,Dye3在甲醇溶液中测得的单分子态吸收曲线 ,当取代基从C2 H5→CH3→无取代基时 ,最大吸收峰对应的波长向短波方向移动 ;乙基取代基的增感染料 (Dye1 )吸附在碘溴化银表面形成的J 聚集态峰值较高 ,对应的增感倍率也高。没有取代基的增感染料 (Dye3)不形成J 聚集 ,增感倍率低 ,有减感作用。Dye4与Dye5相比 ,Dye4具有尖而窄的J 聚集反射光谱 ,增感倍率高。结果表明 :不同结构的增感染料吸附在卤化银颗粒上形成的J 聚集态不同 ,吸收谱带窄的J 聚集态增感染料具有较高的增感倍率。     

免疫算法在车辆调度问题中的应用

免疫算法是模仿生物体高度进化、复杂的免疫系统仿生的一种智能化启发式算法。本文根据车辆调度问题的具体情况，应用免疫算法解决车辆调度中路线安排问题，并提出了一种基于分组匹配的亲和力的计算方法。实验结果表明，免疫算法能有效地应用于车辆调度中路线安排问题。     

基于GARCH模型的石油价格变动模拟

石油是一种特殊的商品,是国家重要的战略物资,世界各国都十分重视其价格变动问题,因为油价变化会影响到各国经济发展,甚至国家安全。因此,本文采用GARCH模型,通过基于Gibbs抽样的MCMC方法分析了国际市场石油价格的分布特征,对石油价格波动的异方差特性进行描述和模拟,实证分析结果说明从石油价格波动序列峰度系数和平方价格波动序列自相关函数的描述来看,基于t分布的模型模拟效果优于基于正态分布的模型,这一结论反映了石油价格波动序列的分布特性。     

可允许集上的广义向量拟均衡问题

主要讨论可允许集上的广义向量拟均衡问题,推广L in的一些结果.