Preparation and electrical conductivity of polyethers/WS2 layered nanocomposites

Utilizing the solvothermal synthesis technique, lithium intercalated tungsten disulfide Li_xWS₂ with x > 1 was obtained, which was allowed to react with water to the formation of single-molecule-layer suspension of tungsten disulfide. The layered nanocomposites PEG, PEO/WS₂, intercalating poly(ethylene glycol) (PEG, MW ≈ 1 × 10³, 6 × 10³, 1 × 10⁴) and poly(ethylene oxide) (PEO, MW ≈ 3 × 10⁵) into the tungsten disulfide host galleries, were prepared using the improved exfoliation-adsorption technique. It was revealed that the intercalated polymers within the host galleries are in a double-layer arrangement with an interlayer expansion of about 9 Å. Despite high conductivity of the host material, those of the PEG, PEO/WS₂ nanocomposites were found to be high in the order of 1 × 10⁻² to 10⁻³ S cm⁻¹ at ambient temperature, resulted from the guest-host charge transfers.     

Synergistic effects of doped Fe3+ and deposited Au on improving the photocatalytic activity of TiO2

Fe³⁺ doped together with Au deposited TiO₂ (Au/Fe³⁺–TiO₂) was successfully prepared, which shows excellent photocatalytic activity for degradation of methyl orange (MO) under both UV and visible light (λ > 420 nm) illumination. Fe³⁺ has been confirmed by EPR to substitute for Ti⁴⁺ in the TiO₂ lattice, and Au exists as Au⁰ on the surface of the photocatalyst indicated by the results of XRD. Fe³⁺ and Au have synergistic effects on improving the photocatalytic activity of TiO₂. A proposed mechanism concerning the synergistic effects is discussed to explain the improvement of the photocatalytic activities.     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

脱硫石膏粉煤灰胶结材水化硬化机理及耐水性研究

以火电厂的两种废渣即脱硫石膏和粉煤灰为主要原料制得的胶结材，其强度明显高于普通石膏制品，软化系数大于０．８５。采用水化热测定、ＸＲＤ和ｐＨ值测定及ＳＥＭ／ＥＤＸＡ分析，并结合宏观试验结果，分析了这种胶结材的水化硬化机理和微结构特点，并对其耐水性提高的原因进行了讨论。     

联合 LTP 和 LPQ 的人脸识别方法

提出一种联合局部三值模式（LTP）和局部相位量化（LPQ）的人脸识别方法,该方法首先对预处理后的人脸分别采用LTP算子、LPQ算子提取各自的直方图,然后,通过特征选择将两者联合为LTP＿LPQ直方图,最后通过最近邻分类器进行分类识别。在ORL和YALE标准人脸数据库上的实验表明,该方法能有效地提高人脸的识别率。     

基于偏序堆的Prim算法设计与实现

本文介绍了借助基于邻接表的偏序堆设计和实现Prim算法的具体方法,文中给出了程序类图、重要数据结构以及关Prim()算法的具体代码,并对算法的执行效率进行分析。     

语音识别中小波分析的应用

语音信号是一种时变、非平稳的随机信号。现有语音识别系统的适应性比较差,尤其在高噪声环境下的语音识别非常困难,若将语音识别系统商品化,还有识别速度、拒识问题以及关键词／句检测技术等细节问题需要解决。如何把语言学、生理学、心理学方面的研究成果量化、建模并用于语音识别,还需深入研究。本文介绍了语音识别中小波分析的研究现状及几种常见的技术方法,并且分析探讨了语音识别中小波分析的应用和发展前景。     

孤立词语音识别技术及其应用前景分析

孤立词语音识别技术,采用的是模式匹配法,是语音识别技术的核心之一。首先,用户将词汇表中的每一词依次说一遍,并且将其特征矢量作为模板存入棋板库。然后,将输入语音的特征矢量依次与模板库中的每个模板进行相似度比较,将相似度最高者作为识别结果输出。本文介绍了孤立词语音识别技术的研究现状及几种常见的技术方法,并且分析探讨了孤立词语音识别技术的应用和发展前景。     

On adaptive sliding mode control without switching gain overestimation

This paper presents some further results on adaptive sliding mode control (ASMC) for a class of nonlinear systems with bounded uncertain parameters. Given a large initial tracking error, current ASMC design generally produces an unnecessarily large switching gain, consequently leading to a serious chattering problem or a large‐amplitude control jump for the continuous counterpart. To solve such an overadaptation problem, the switching gain adaptation mechanism is first analyzed in this paper, and the adaptation induced by the initial tracking error is suggested to be removed. Then, by exploiting the global sliding mode feature of time‐varying sliding mode control and integral sliding mode control, we present two effective methodologies for ASMC design. The proposed ASMC algorithms ensure that there is no overestimation of the switching gain and the system response is not slowed down when a small switching gain is generated. The validity of the proposed methods is verified by both theoretical analysis and simulation results. Copyright © 2012 John Wiley & Sons, Ltd.     

An expressive framework and efficient algorithms for the analysis of collaborative tagging

The rise of Web 2.0 is signaled by sites such as Flickr, del.icio.us, and YouTube, and social tagging is essential to their success. A typical tagging action involves three components, user, item (e.g., photos in Flickr), and tags (i.e., words or phrases). Analyzing how tags are assigned by certain users to certain items has important implications in helping users search for desired information. In this paper, we develop a dual mining framework to explore tagging behavior. This framework is centered around two opposing measures, similarity and diversity, applied to one or more tagging components, and therefore enables a wide range of analysis scenarios such as characterizing similar users tagging diverse items with similar tags or diverse users tagging similar items with diverse tags. By adopting different concrete measures for similarity and diversity in the framework, we show that a wide range of concrete analysis problems can be defined and they are NP-Complete in general. We design four sets of efficient algorithms for solving many of those problems and demonstrate, through comprehensive experiments over real data, that our algorithms significantly out-perform the exact brute-force approach without compromising analysis result quality.