线型聚(N-杂环化)硅烷体系的电子结构与光谱性质的比较研究

用密度泛函理论(DFT)和含时密度泛函理论(TD-DFT)对线型(N-杂环化)硅烷低聚体系与简单聚硅烷的电子结构和吸收光谱性质进行了比较研究。对各体系的基态分子结构在B3LYP/6-31G**水平上进行了全优化,讨论了电荷分布和前线分子轨道性质。在获得基态稳定构型的基础上,应用含时密度泛函理论计算了电子吸收光谱的性质。计算结果显示,当主链硅原子被氮杂环环化后,由于空间位阻作用使相邻硅硅键明显伸长,使主链结构变得松散。但同时改善了分子主链的电子离域范围,增强了分子结构的可塑性。随着氮杂环数目的增加,低聚硅烷的电子吸收光谱发生明显的红移。氮杂环的引入对聚硅烷的最大吸收光谱带影响非常大。     

Mining disjunctive minimal generators with TitanicOR

Disjunctive minimal generators were proposed by Zhao, Zaki, and Ramakrishnan (2006). They defined disjunctive closed itemsets and disjunctive minimal generators through the disjunctive support function. We prove that the disjunctive support function is compatible with the closure operator presented by Zhao et al. (2006). Such compatibility allows us to adapt the original version of the Titanic algorithm, proposed by Stumme, Taouil, Bastide, Pasquier, and Lakhal (2002) to mine iceberg concept lattices and closed itemsets, to mine disjunctive minimal generators. We present TitanicOR, a new breadth-first algorithm for mining disjunctive minimal generators. We evaluate the performance of our method with both synthetic and real data sets and compare TitanicOR’s performance with the performance of BLOSOM (Zhao et al., 2006), the state of the art method and sole algorithm available prior to TitanicOR for mining disjunctive minimal generators. We show that TitanicOR’s breadth-first approach is up to two orders of magnitude faster than BLOSOM’s depth-first approach.     

利用角点历史信息的异常行为识别算法

针对视频监控场景中的异常行为事件,如突然的奔跑、人群的异常聚集等现象,提出一种利用角点运动历史图策略的行为识别算法,即首先通过角点提取算法进行场景角点提取;然后通过时间累积获取角点的历史图,通过角点历史图将场景中的角点划分为静态角点和动态角点;最后通过动态角点分析完成监控场景异常行为分析识别。新算法充分利用了图像的时空信息,并且克服了场景光照影响,增强了异常行为检测与识别的准确性。通过真实场景实验可以看出,新算法能够对不同监控场景的异常行为进行准确检测,并且其检测速度快,满足实际应用需求。     

二元及三元过渡金属氧化物的制备及其电化学应用研究进展

二元及三元过渡金属氧化物由于其优异的物理和化学特性,在电化学领域得到了广泛的应用。本文主要介绍了不同元素组成的二元及三元过渡金属氧化物,以及通过不同制备方法得到的空心球状、管状、片状、立方体、棒状、针状、伞形等多种不同形貌的二元及三元过渡金属氧化物;总结了二元及三元过渡金属氧化物在超级电容器、锂离子电池和传感器领域中表现出的优异性能;最后对二元及三元过渡金属氧化物的应用前景进行了展望。     

Fast wireless sensor for anomaly detection based on data stream in an edge-computing-enabled smart greenhouse

Edge-computing-enabled smart greenhouses are a representative application of the Internet of Things (IoT) technology, which can monitor the environmental information in real-time and employ the information to contribute to intelligent decision-making. In the process, anomaly detection for wireless sensor data plays an important role. However, the traditional anomaly detection algorithms originally designed for anomaly detection in static data do not properly consider the inherent characteristics of the data stream produced by wireless sensors such as infiniteness, correlations, and concept drift, which may pose a considerable challenge to anomaly detection based on data stream and lead to low detection accuracy and efficiency. First, the data stream is usually generated quickly, which means that the data stream is infinite and enormous. Hence, any traditional off-line anomaly detection algorithm that attempts to store the whole dataset or to scan the dataset multiple times for anomaly detection will run out of memory space. Second, there exist correlations among different data streams, and traditional algorithms hardly consider these correlations. Third, the underlying data generation process or distribution may change over time. Thus, traditional anomaly detection algorithms with no model update will lose their effects. Considering these issues, a novel method (called DLSHiForest) based on Locality-Sensitive Hashing and the time window technique is proposed to solve these problems while achieving accurate and efficient detection. Comprehensive experiments are executed using a real-world agricultural greenhouse dataset to demonstrate the feasibility of our approach. Experimental results show that our proposal is practical for addressing the challenges of traditional anomaly detection while ensuring accuracy and efficiency.     

黏弹性复合材料阻尼板的振动特性

为深入探索黏弹性复合材料阻尼板的振动特性,基于复合材料力学理论、一阶剪切变形理论、分段位移模型以及哈密尔顿原理,推导了黏弹性复合材料阻尼板结构复数形式的振动微分方程。采用纳维法得到满足位移边界条件的理论解,通过有限元建模仿真对理论解进行验证。基于验证过的理论模型,进一步从理论上探索了黏弹性复合材料阻尼板振动特性随结构参数的变化规律。     

“一网双平面”—一种新的广域骨干网络架构

“一网双平面”架构是广域骨干承载平台架构的一种。通过将广域骨干承载平台的骨干网络划分为两个逻辑独立的环网,形成“一个骨干网络、两个平面(转发平面和控制平面)”的一种新的网络架构。     

瓦楞原纸环压增强剂的合成与应用研究

合成了新型乳液型瓦楞原纸环压增强剂KLZ-15．采用旧瓦楞纸箱（OCC）纸浆,在不同的助剂-纸浆接触时间、助剂用量、湿压榨压力等条件下,与传统的阳离子聚丙烯酰胺、阳离子淀粉增强剂进行应用效果比较．结果表明三种助剂都具有较好的增环压效果,乳液型增强剂的效果明显表现为最佳,其次为阳离子聚丙烯酰胺,再次为阳离子淀粉．     

Energetics and diffusional properties of He in BCC Mo: An empirical potential for molecular dynamics simulations

This paper presents an interatomic potential for modeling He defects and bubbles in body-centered-cubic (BCC) Mo. We utilize three existing frameworks: the Finnis–Sinclair (FS) potential for Mo–Mo, the Effective-Medium-Theory (EMT) for He–Mo, and the Hartree–Fock-Dispersion (HFD) potential for He–He interactions. The energetics of He defects and the diffusivity of He interstitial given by this potential agree well with ab initio calculations and experimental measurements. Furthermore, in agreement with theoretical prediction, it is shown that the introduction of He gas suppresses the surface diffusivity of BCC Mo, which decays exponentially with increasing He pressure acting on the free surface. The decay constant, correlated with the characteristic interaction volume for He–Mo, is close to the atomic volume of BCC Mo. This suppression effect is important to understand the mobility of small He bubbles.     

Flame synthesis of carbon nanotubes and few-layer graphene on metal-oxide spinel powders

Multi-walled and single-walled carbon nanotubes (CNTs) and few-layer graphene (FLG) are grown directly on spinel powders using flame synthesis. CNT and FLG growth occurs via the decomposition of flame-generated carbon precursors (e.g., CO, C₂H₂, and CH₄) over nanoparticles (i.e., Ni, Co, Fe, and Cu) reduced from the solid oxide. The growth of CNTs is investigated on NiAl₂O₄, CoAl₂O_4, and ZnFe₂O₄, using counterflow diffusion flame and multiple inverse-diffusion flames (m-IDFs), while the growth of FLG is investigated on CuFe₂O₄ using m-IDFs. As shown by analytical electron microscopy techniques, Raman spectroscopy, and X-ray diffraction, substrate temperature and spinel composition play critical roles in the growth of both CNTs and FLG.