Multi-label classification via learning a unified object-label graph with sparse representation

Automatic annotation is an essential technique for effectively handling and organizing Web objects (e.g., Web pages), which have experienced an unprecedented growth over the last few years. Automatic annotation is usually formulated as a multi-label classification problem. Unfortunately, labeled data are often time-consuming and expensive to obtain. Web data also accommodate much richer feature space. This calls for new semi-supervised approaches that are less demanding on labeled data to be effective in classification. In this paper, we propose a graph-based semi-supervised learning approach that leverages random walks and ? ₁ sparse reconstruction on a mixed object-label graph with both attribute and structure information for effective multi-label classification. The mixed graph contains an object-affinity subgraph, a label-correlation subgraph, and object-label edges with adaptive weight assignments indicating the assignment relationships. The object-affinity subgraph is constructed using ? ₁ sparse graph reconstruction with extracted structural meta-text, while the label-correlation subgraph captures pairwise correlations among labels via linear combination of their co-occurrence similarity and kernel-based similarity. A random walk with adaptive weight assignment is then performed on the constructed mixed graph to infer probabilistic assignment relationships between labels and objects. Extensive experiments on real Yahoo! Web datasets demonstrate the effectiveness of our approach.     

Tracking Performance Bound with Finite Control Energy and Erasure Channel Energy Constraint

This paper studies the tracking performance of the single‐input single‐output (SISO), finite dimensional, linear and time‐invariant (LTI) system under the channel input energy constraint over the Erasure channel. A new performance index is proposed which is minimized over all two‐degree‐of‐freedom stabilizing controllers. The explicit expressions of the lower bound of the performance index and the minimum of the signal‐to‐noise ratio are obtained. The results show that the performance bound is correlated to unstable poles, non‐minimum phase zeros and the packet loss probability. Finally, examples are given to validate the conclusions derived.     

Adaptive Tracking Control for Nonlinear Systems with a Class of Input Nonlinearities

An adaptive tracking control approach is presented for nonlinear systems with a class of input nonlinearities. A generalized model has been developed for a class of non‐smooth nonlinearities that include dead‐zone, backlash and ‘backlash‐like’ hysteresis. By using the developed model and Nussbaum‐gain technique, the problem of input nonlinearity is solved perfectly. The proposed method is available even when the designer is uncertain about the type of input nonlinearities mentioned above, and the knowledge on the bounds of these nonlinearity parameters is not required. Furthermore, it is proved that all closed‐loop signals are bounded and the tracking error converges to a small residual set asymptotically. Two simulation examples are provided to demonstrate the effectiveness of the proposed method.     

Yang–Baxter equations and quantum entanglements

In this paper some results associated with a new type of Yang–Baxter equation (YBE) are reviewed. The braiding matrix of Kauffman–Lomonaco has been extended to the solution (called type-II) of Yang–Baxter equation (YBE) and the related chain Hamiltonian is given. The Lorentz additivity for spectral parameters is found, rather than the Galilean rule for the familiar solutions (called type-I) of YBE associated with the usually exact solvable models. Based on the topological basis, the N-dimensional solution of YBE is found to be the Wigner D-functions. The explicit examples for spin-\(\frac{1}{2}\) and spin-1 have been shown. The extremes of \(\ell _1\)-norm of \(D\)-functions are introduced to distinguish the type-I from type-II of braiding matrices that also correspond to those of von Neumann entropy for quantum information.     

Protection of quantum correlations against decoherence

The protection of different quantum correlations, such as Bell nonlocality, quantum discord, and geometric quantum discord as trace distance against noise, is explored. By weak measurement and quantum measurement reversal, we show that the mentioned quantum correlations can be effectively preserved probabilistically from the decoherence due to amplitude damping. The results will play an important role in the experiments using the quantum correlations as resource.     

基于Spark框架的乘潮水位计算与可视化平台

乘潮水位计算是海洋环境信息处理的重要组成部分,具有计算量大、计算复杂度高、计算时间长等特性。采用传统集群计算模式实现乘潮水位计算业务,存在计算成本高、计算伸缩性和交互性差的问题。针对以上问题,提出一种基于Spark框架的乘潮水位计算和可视化平台。结合对Spark任务调度算法的研究,设计和实现了一种基于节点计算能力的任务调度算法,实现了长时间序列的多任务乘潮水位数据的检索、获取、数值计算、特征可视化的并行处理,达到了海量海洋环境数据计算和可视化处理的目的。实验结果表明,提出的基于Spark的乘潮水位计算和可视化平台可以有效地提高海量乘潮水位数据的分布式并行处理的效率,为更加快速和高效的乘潮水位计算提供了一种新的方法。     

岩土工程勘察的重点分析

近年来,岩土工程勘察技术发展得非常快,研究领域不断拓展,取得了较多的成就。但是,在发展过程中也存在一些不足。重点分析了岩土工程勘察工作,并结合实际工作提出一些个人意见,以期能为相关工作提供帮助。     

基于CDIO教育理念的高职计算机应用技术专业课程标准研究与实践

课程标准的制定有利于教师明确课程的目标、内容、教学方法、考核方式,并能指导教学设计、规范课程教学过程,培养学生的职业能力。本文以《.NET网站开发》课程为例,从职业岗位(群)的调研,分析归纳出课程的职业能力,确定课程的教学项目,结合相关职业资格标准,设计教学详细内容、教学方法和手段等,最终完成课程标准的制定。     

智能卡COS操作系统高速下载的研究与实现

随着信息化时代的到来,智能卡作为信息化技术标志之一,在金融等方面的应用逐渐普及。智能卡操作系统不同于传统软件,它工作在嵌入式环境,具有硬件资源有限、工作环境不稳定等特点,所以其设计方法与传统方法有所不同。智能卡操作系统在投入使用之前,必须经过严格的测试,这是由嵌入式系统工作的特性决定的,因为当软件工作后出现漏洞时很难进行弥补。本文通过对智能卡下载机制的研究,改进设计以提高智能卡操作系统的下载速度,进而提高测试效率和缩短发卡时间。