Designing Metallic and Insulating Nanocrystal Heterostructures to Fabricate Highly Sensitive and Solution Processed Strain Gauges for Wearable Sensors

All‐solution processed, high‐performance wearable strain sensors are demonstrated using heterostructure nanocrystal (NC) solids. By incorporating insulating artificial atoms of CdSe quantum dot NCs into metallic artificial atoms of Au NC thin film matrix, metal–insulator heterostructures are designed. This hybrid structure results in a shift close to the percolation threshold, modifying the charge transport mechanism and enhancing sensitivity in accordance with the site percolation theory. The number of electrical pathways is also manipulated by creating nanocracks to further increase its sensitivity, inspired from the bond percolation theory. The combination of the two strategies achieves gauge factor up to 5045, the highest sensitivity recorded among NC‐based strain gauges. These strain sensors show high reliability, durability, frequency stability, and negligible hysteresis. The fundamental charge transport behavior of these NC solids is investigated and the combined site and bond percolation theory is developed to illuminate the origin of their enhanced sensitivity. Finally, all NC‐based and solution‐processed strain gauge sensor arrays are fabricated, which effectively measure the motion of each finger joint, the pulse of heart rate, and the movement of vocal cords of human. This work provides a pathway for designing low‐cost and high‐performance electronic skin or wearable devices.     

A review on mechanisms and recent developments of nanomaterials based carbon fiber reinforced composites for enhanced interface performance

Carbon fiber reinforced composites have attracted lots of attention in many fields. However, on account of the poor infiltration of resin to carbon fiber, the weak interface performance between fiber and resin has been restricting the interface properties of composites. In recent progress, the review attaches more importance to the introduction of the third phase monomer, which mainly uses physical and chemical methods to assemble nanomaterials (such as carbon nanotubes, graphene, etc.) on the carbon fiber surface to modify the interface structure of the carbon fiber reinforced composites, and all of them have been demonstrated in this paper. Furthermore, the effects of introducing nanomaterials on the structure of the fiber/resin interface and the relationship between multi-scale interface structure and properties have been investigated. It can be seen that the design idea of researchers mainly uses one or more theories to improve the interface properties of carbon fiber reinforced composites, such as transition layer, chemical bonding, mechanical interlocking, infiltration, diffusion, and adsorption. In brief, this work provides some novel insights for the preparation of carbon fiber reinforced composites with excellent interlaminar shear strength.     

Theory and techniques of data mining in CGF behavior modeling

For the large quantity of data,rules and models generated in the course of computer generated forces (CGFs) behavior modeling,the common analytical methods are statistical methods based on the tactical rules,tactical doctrine and empirical knowledge.However,from the viewpoint of data mining,we can find many of these analytical methods are also each-and-every different data mining methods.In this paper,we survey the data mining theory and techniques that have appeared in the course of CGF behavior modeling f...     

Stability analysis for multi-agent systems using the incidence matrix: Quantized communication and formation control

The spectral properties of the incidence matrix of the communication graph are exploited to provide solutions to two multi-agent control problems. In particular, we consider the problem of state agreement with quantized communication and the problem of distance-based formation control. In both cases, stabilizing control laws are provided when the communication graph is a tree. It is shown how the relation between tree graphs and the null space of the corresponding incidence matrix encode fundamental properties for these two multi-agent control problems.     

A characterization of (regular) circular languages generated by monotone complete splicing systems

Circular splicing systems are a formal model of a generative mechanism of circular words, inspired by a recombinant behaviour of circular DNA. Some unanswered questions are related to the computational power of such systems, and finding a characterization of the class of circular languages generated by circular splicing systems is still an open problem. In this paper we solve this problem for monotone complete systems, which are finite circular splicing systems with rules of a simpler form. We show that a circular language L is generated by a monotone complete system if and only if the set Lin(L) of all words corresponding to L is a pure unitary language generated by a set closed under the conjugacy relation. The class of pure unitary languages was introduced by A. Ehrenfeucht, D. Haussler, G. Rozenberg in 1983, as a subclass of the class of context-free languages, together with a characterization of regular pure unitary languages by means of a decidable property. As a direct consequence, we characterize (regular) circular languages generated by monotone complete systems. We can also decide whether the language generated by a monotone complete system is regular. Finally, we point out that monotone complete systems have the same computational power as finite simple systems, an easy type of circular splicing system defined in the literature from the very beginning, when only one rule of a specific type is allowed. From our results on monotone complete systems, it follows that finite simple systems generate a class of languages containing non-regular languages, showing the incorrectness of a longstanding result on simple systems.     

改进的证据理论在合作频谱感知中的应用

为了能够在认知无线电网络中有效、准确地检测出授权用户,提出了基于改进的证据理论的合作频谱感知方案设计方法.根据各个次用户对授权用户进行多次本地检测得出的时域DS融合结果,设计并改进融合顺序和融合结构,将多个时域DS融合结果送到融合中心进行空域DS融合,得到最终判决.在此基础上,给出了融合顺序、融合结构的改变对算法性能的...     

网络演算的矩阵解释

网络演算是离散事件动态系统理论在计算机网络中的应用,网络演算通过到达曲线和服务曲线计算网络的性能参数,这两个概念封装了复杂的理论背景,从而易于在实际中应用,但对到达曲线和服务曲线概念的理论研究比较缺乏.文中采用幂等矩阵的角度描述到达曲线和服务曲线,演算的过程成为矩阵运算,通过结合矩阵双子理论和余理论的研究结果,得出了由矩阵表演算的基本定理.研究表明,幂等矩阵理论为网络演算提供了很好的理论解释.文中还提出一种基于变换矩阵的方法求某些网络元素的服务曲线.     

移动自组网中非完全信息节点风险评估

移动自组网是一种无中心、自组织以及多跳的无线网络,能否有效可靠地对通信节点进行风险评估是保障节点高质量通信的重要因素.当前基于可信度或是信誉的评估方法对评估样本都有特殊的要求,对评估对象提出种种假设,无法辨别间接样本的恶意推荐问题,在实际移动自组网中各个节点尤其是恶意节点对外暴漏的信息往往偏少,样本数量有限,无法明确判断其状态,大部分是非完全信息,从而导致评估结果缺乏客观性与可靠性.文中提出采用灰色系统理论描述通信节点非完全信息状态,根据灰类白化以及灰色聚类思想进行节点风险评估.方案针对自组网络通信需求对节点行为进行多关键属性划分,采用味集群方法收集原始样本,避免恶意推荐;将难以用数值精确刻画的关键属性以白化权函数量化,引入灰聚类的概念和计算方法,将实体的通信风险水平定义为实体关键属性值序列针对各评估灰类的聚类评估值,从而得到该实体通信风险水平的相对参考值.分析与实际计算表明该方法是一种适合移动自组网中非完全信息节点风险评估的有效方法.     

Combining feature spaces for classification

In this paper we offer a variational Bayes approximation to the multinomial probit model for basis expansion and kernel combination. Our model is well-founded within a hierarchical Bayesian framework and is able to instructively combine available sources of information for multinomial classification. The proposed framework enables informative integration of possibly heterogeneous sources in a multitude of ways, from the simple summation of feature expansions to weighted product of kernels, and it is shown to match and in certain cases outperform the well-known ensemble learning approaches of combining individual classifiers. At the same time the approximation reduces considerably the CPU time and resources required with respect to both the ensemble learning methods and the full Markov chain Monte Carlo, Metropolis-Hastings within Gibbs solution of our model. We present our proposed framework together with extensive experimental studies on synthetic and benchmark datasets and also for the first time report a comparison between summation and product of individual kernels as possible different methods for constructing the composite kernel matrix.