凹凸棒粘土用作高水速凝注浆悬浮剂

以凹凸棒粘土作为高水速凝固化充填材料的悬浮稳定剂，考察了不同制浆机械对凹凸棒粘土制浆率的影响。采用高剪切混合乳化机预制的1％凹凸棒粘土浆配制高水速凝固化充填材料甲、已料单浆可获得满意的悬浮稳定效果。其充填体结石抗压强度早期发展迅速，后期持续增长。采用此工艺，注浆料的材料成本仅增加2％。     

Generalized Transfer Subspace Learning Through Low-Rank Constraint

It is expensive to obtain labeled real-world visual data for use in training of supervised algorithms. Therefore, it is valuable to leverage existing databases of labeled data. However, the data in the source databases is often obtained under conditions that differ from those in the new task. Transfer learning provides techniques for transferring learned knowledge from a source domain to a target domain by finding a mapping between them. In this paper, we discuss a method for projecting both source and target data to a generalized subspace where each target sample can be represented by some combination of source samples. By employing a low-rank constraint during this transfer, the structure of source and target domains are preserved. This approach has three benefits. First, good alignment between the domains is ensured through the use of only relevant data in some subspace of the source domain in reconstructing the data in the target domain. Second, the discriminative power of the source domain is naturally passed on to the target domain. Third, noisy information will be filtered out during knowledge transfer. Extensive experiments on synthetic data, and important computer vision problems such as face recognition application and visual domain adaptation for object recognition demonstrate the superiority of the proposed approach over the existing, well-established methods.     

合成氢化松香乙酯的新工艺研究

以DRC为催化剂,在无溶剂条件下,通过氢化松香与乙醇的直接酯化反应合成氢化松香乙酯。探索了反应温度、催化剂用量、反应时间、物料配比等因素对反应酯化率的影响,确定最佳反应条件为:反应温度180℃,催化剂用量为原料氢化松香质量的6%,反应时间6h,醇与酸的摩尔比为3∶1。在最佳条件下酯化率达92.2%。还探讨了用阴离子交换树脂柱层析分离纯化氢化松香乙酯粗产物的方法。此外,利用红外光谱对氢化松香乙酯精制产物进行了表征;用GC-MS分别对氢化松香乙酯粗产物及其精制产物进行了定性和定量分析,比较了柱层析前后化学组成的变化。     

Tactile display with tangential and normal skin displacement for robot-assisted surgery

This paper proposes a tactile display providing both shear and normal feedback to the fingertip for generating three-axis tactile feedback during teleoperation of a surgical robot. The display is composed of five balloons actuated by controlling the pneumatic pressure. The implemented display is 18?mm?×?18?mm?×?15?mm. This size is suitable for mounting the display onto the master controls of a surgical robot. The maximum normal and shear displacements are 2 and 1.3?mm, respectively. The proposed tactile display may provide perceivable stimuli to a human finger pad in all five directions: normal, distal, proximal, radial, and ulnar. This paper also reports on the results of psychophysical measurement of the minimum perceivable movement of the developed tactile display for each of the five directions.     

Mining top-k frequent patterns with combination reducing techniques

Top-k frequent pattern mining finds interesting patterns from the highest support to the k-th support. The approach can be effectively applied in numerous fields such as marketing, finance, bio-data analysis, and so on since it does not need constraints by a minimum support threshold. Top-k mining methods use the support of the k-th pattern, not a user-specified minimum support. Thus, the methods conduct mining operations based on very low supports until the k-th pattern is detected. When a low support is used in the mining process, single-paths with numerous items are generated, where the top-k mining algorithm extracts valid patterns by combining the items for each single-path. Therefore, the bigger the number of combinations is, the larger the increase in time and memory consumption is. In this paper, in order to mine top-k frequent patterns more efficiently, we consider converting patterns obtained from single-paths into composite patterns during the mining process and recovering them as the original patterns when the top-k frequent patterns are extracted. For this, we define a new concept, the composite pattern, and propose novel techniques for reducing pattern combinations in the single-path. Two algorithms are introduced in this paper, where the former is CRM (Combination Reducing method), applying our reduction manner, and the latter is CRMN (Combination Reducing method for N-itemset), considering N-itemset, i.e., patterns’ lengths. A performance evaluation shows that CRM and CRMN algorithms can efficiently reduce pattern combinations in single-paths compared to state-of-the-art algorithms. The experimental results also illustrate that our approaches have outstanding performance in terms of runtime, memory, and scalability.     

Study of collective user behaviour in Twitter: a fuzzy approach

The study of collective user behaviours in social networking sites has become an increasing important topic in social media mining. Understanding such behaviours has its potential to extract actionable patterns that can be beneficial to develop effective marketing strategies, optimise user experiences and maximise website revenues. With the rapid development of micro-blogging, Twitter has become a richer source of intelligence that can be used to study collective user behaviour, due to its efficient and meaningful user-to-user interactions. However, the classical statistical methods have some drawbacks in bridging the gap between user-generated data and human analysts who mostly use linguistic terms to analyse data and model/summarise knowledge learned. To address this gap, this work proposes a new approach, which employs the mass assignment theory-based fuzzy association rules algorithm (MASS-FARM), for the first time, to extract useful interaction behaviour of Twitter users. The influential factors (including activity time, number of friends/followers and the number of tweets) are represented as fuzzy granules, and the associations amongst are studied by employing MASS-FARM. The collective user behaviours are analysed in the Reply category and the Non-Reply category, respectively. The applicability and usefulness of the proposed method are demonstrated via an empirical study on a collected Twitter data set. The derived results are also discussed and compared with existing works.     

煤中吡啶型氮热解机理的量子化学研究

用密度泛函 ( DFT)方法 ,在 UB3LYP/6- 31 G( d)水平上研究了煤中吡啶型氮的热解机理 ,对热解过程中由于官能团周围环境的不同而形成的三类吡啶自由基进行了量子化学计算 ,通过对键的 Mulliken布居数等计算结果的分析 ,分别得到了这三类自由基的热解途径 .并优化得到了反应物、中间体和产物的几何构型 .计算结果表明 ,吡啶型氮主要是以 HCN的形式释放出来的 .NH3 是 HCN二次反应的产物 .     

宽带功率放大器PGSC建模方法及预失真研究

针对宽带功率放大器的强记忆效应特性,提出一种功放建模和数字预失真方法——PGSC模型。利用广义记忆多项式(GMP)、特定交叉项(SCT)及记忆时刻信号交叉项(CIMT)3个基函数来构造功放行为模型及数字预失真器,并搭建实际测试平台对模型的精度及线性化效果进行验证。测试结果表明,与PMEC方法相比,PGSC方法建模时的归一化均方误差减少了2.1 dB,数字预失真时输出信号的三阶邻信道功率比降低了4.94/2.03 dB;与GMP方法相比,PGSC方法仅利用73%的系数即可得到更高的模型精度和更好的线性化效果。     

原材料价格波动下钢铁生产库存多期优化模型

考虑钢铁企业钢材生产受钢材需求和生产变动成本波动的双重影响,在预测基础上,建立钢材生产库存多期动态优化模型。由于模型涉及多种钢材及多个时段,属于大规模问题,求解困难,且为了避免粒子群算法陷入局部最优,提出采用模拟退火与粒子群组合智能算法对模型进行求解。最后通过钢铁企业L的案例,结果表明算法具有较强的收敛性和适用性,模型可用于解决钢铁企业多期生产实际问题。     

一种林业手持式多功能测树仪设计

针对森林调查对便携式测量设备自动化和集成化的需求,设计了一种集测高器、角规和标准蓄积量计算功能于一体,具有测量、数据存储、计算等多种功能的手持式多功能电子测树仪GForest。该仪器通过采样控制算法实现对测高器防抖动设计,采用计数器存储并控制角规计数结果,提供USB接口同PC和移动智能终端设备进行数据共享,旨在解决目前森林地面调查数据采集硬件设备信息化与数据采集软件发展不同步的问题,大幅减少了外业调查中手工数据记录和录入的工作,提高了野外数据采集的效率。经实测验证:GForest测得的立木高度与实际值的平均误差为4%,与进口同类设备精度持平,同时还具有角规绕测计数与控制等实用功能,且具有明显的成本优势,适合在行业内推广应用。