Advanced Functional Materials Constructed from Pillar[n]arenes

Pillar[n]arenes are new generation of supramolecular macrocyclic host, which exhibit excellent host−guest recognition properties. In the last decade, functional materials constructed from pillar[n]arenes have been attracted more and more attention and displayed outstanding characteristics, such as stimuli-responsiveness, self-healing and adaptability. In this mini-review, we provide a survey of the pillar[n]arene-based literatures covering light-harvesting systems, functional hydrogels, and solid materials. It is anticipated that more and more pillar[n]arenes-based advanced materials with multi-functional properties will appear in the near future.     

A novel spectrum sensing scheme with sensing time optimization for energy-efficient CRSNs

Wireless Networks - The cognitive radio technology enables secondary users (SUs) to occupy licensed bands when primary users (PUs) are not occupy them. Spectrum sensing is a key technology for SUs...     

基于LP与小波包的复杂机电系统监测序列混沌降噪方法

针对流程工业生产系统监测数据存在强噪声和混沌性的特点,提出了一种局部投影方法(Local Projection Method)与小波包方法相结合的信号降噪方法。该方法先利用局部投影方法从动力学系统嵌入流形的角度进行多次迭代降噪,并根据关联维数来判定迭代终止;再利用小波包方法从频率的角度进行降噪,抑制高频噪声的干扰,取得了较好的降噪效果。用Lorenz时间序列进行仿真验证,对仿真时间序列加入不同程度的噪声,对比分析小波包、局部投影与该方法降噪后的相空间、SNR值和最大Lyapunov指数,证明了该方法对于中高强度噪声具有更好的降噪效果。并将该方法用于某压缩机组的实际监测数据降噪,评估三种方法的降噪效果,进一步验证了该方法的优越性。     

带权决策表的属性约简

属性约简是粗糙集理论的重要应用。考虑将决策表中的每行都作为一条决策规则时，若把表中出现相同决策规则的次数作为权，可得到带权决策表。提出了关于带权决策表的正域约简相应的辨识矩阵并给出了证明，从而得到了约简算法。相比于决策表中的正域约简时发现，通过将决策表转化为带权决策表后，再利用算法1进行约简时，其在一定程度上优于前者。提出了近似分类精度约简相应的辨识矩阵并给出了证明。对于2个算法，在选取的UCI数据集上进行了实验验证。通过实验进一步说明了所提出算法的可行性和有效性。     

Stability and stabilization for singularly perturbed systems with Markovian jumps

This article focuses on the stability and stabilization problems of singularly perturbed jump systems. Here, the singularly perturbed parameter (SPP) is also with Markov switching and satisfies any with positive bound predefined. First, stability conditions expressed ?_i‐free but involving its bound are developed by constructing an ?_i‐dependent Lyapunov function. Then, a method for state feedback stabilization controller depending on SPP is proposed, whose conditions are given in terms of linear matrix inequalities. Moreover, some special cases about deterministic SPP are considered too. Finally, two practical examples are used to demonstrate the effectiveness and superiorities of the proposed methods.     

Hierarchical Deep Neural Network for Image Captioning

Neural Processing Letters - Automatically describing image content with natural language is a fundamental challenge for computer vision community. General methods used visual information to...     

An experimental study of relative total variation and probabilistic collaborative representation for iris recognition

Multimedia Tools and Applications - Iris images collected under different conditions often suffer from specular reflections, cast shadows, motion blur, defocus blur, occlusion caused by eyelashes...     

Popularity prediction of movies: from statistical modeling to machine learning techniques

Multimedia Tools and Applications - Film industries all over the world are producing several hundred movies rapidly and grabbing the attraction of people of all ages. Every movie producer is of...