一种新的知觉分割模型*

根据知觉的最新理论研究和实验结果,提出一种新的知觉模型,并用于考查计算机视觉中的分割问题.分割问题实质上是知觉表达问题,现在分割的困难性可能是知觉上局部到整体的还原论假设造成的;分割可能不是一次完成的,而是经过整体到局部的过程才最终完成.新的知觉模型将对建立更好的分割模型提供理论基础.     

CORBA技术在现场设备通信中的应用*

首先简要介绍CORBA体系结构,阐述了利用CORBA的代理机制,通过代理屏蔽不同通信协议差异,以实现设备之间通信的集成策略.该机制能够方便地实现不同协议设备之间的通信集成,而且便于系统扩展,并兼容多种操作系统平台.最后结合具体实例给出现场设备的集成方案.     

In-Plane Cracking Behavior and Ultimate Strength for 2D Woven and Braided Melt-Infiltrated SiC/SiC Composites Tensile Loaded in Off-Axis Fiber Directions

The tensile mechanical properties of ceramic matrix composites (CMC) in directions off the primary axes of the reinforcing fibers are important for the architectural design of CMC components that are subjected to multiaxial stress states. In this study, two-dimensional (2D)-woven melt-infiltrated (MI) SiC/SiC composite panels with balanced fiber content in the 0° and 90° directions were tensile loaded in-plane in the 0° direction and at 45° to this direction. In addition, a 2D triaxially braided MI SiC/SiC composite panel with a higher fiber content in the ±67° bias directions compared with the axial direction was tensile loaded perpendicular to the axial direction tows (i.e., 23° from the bias fibers). Stress–strain behavior, acoustic emission, and optical microscopy were used to quantify stress-dependent matrix cracking and ultimate strength in the panels. It was observed that both off-axis-loaded panels displayed higher composite onset stresses for through-thickness matrix cracking than the 2D-woven 0/90 panels loaded in the primary 0° direction. These improvements for off-axis cracking strength can in part be attributed to higher effective fiber fractions in the loading direction, which in turn reduces internal stresses on weak regions in the architecture, e.g., minicomposite tows oriented normal to the loading direction and/or critical flaws in the matrix for a given composite stress. Both off-axis-oriented panels also showed relatively good ultimate tensile strength when compared with other off-axis-oriented composites in the literature, both on an absolute strength basis as well as when normalized by the average fiber strength within the composites. Initial implications are discussed for constituent and architecture design to improve the directional cracking of SiC/SiC CMC components with MI matrices.     

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 .