基于网络图像的阿奇姆博多拼图

拼图是使用不同形式的素材进行组装的合成艺术.文中介绍了一种崭新的拼图创作方法,通过挑选主题相关的网络图像的前景抠图来表现一幅输入图像,能够生成奇异的具有阿奇姆博多风格的拼图.鉴于网络图像数据的海量规模,总能够找到合适的前景抠图来匹配输入图像的各个分割部分;通过将挑选的前景抠图按照一定的规则进行组装,使其在整体上可以从形状和颜色表现输入图像,而在局部每个前景抠图仍然可以辨识.实验结果和用户体验表明,采用文中方法可以有效地生成具有娱乐性的阿奇姆博多拼图.     

面向高端装备制造CAE技术的机遇和挑战

针对高端装备制造在设计、分析、制造、服役和维护等全过程中对CAE的需求,从结构、流体以及流固耦合等3个方面概述CAE技术国内外进展及其面临的机遇和挑战,指出在发展具有能够对装备在极端服役环境下准确的结构、流体和流固耦合CAE分析技术的基础之上,需不断突破面向工程应用的多物理场耦合、跨尺度分析、多学科综合设计、产品性能评估和集成等关键技术,使CAE逐步向支持现代设计和全寿命周期管理转变.     

RAFNet: RGB-D attention feature fusion network for indoor semantic segmentation

Semantic segmentation based on the complementary information from RGB and depth images has recently gained great popularity, but due to the difference between RGB and depth maps, how to effectively use RGB-D information is still a problem. In this paper, we propose a novel RGB-D semantic segmentation network named RAFNet, which can selectively gather features from the RGB and depth information. Specifically, we construct an architecture with three parallel branches and propose several complementary attention modules. This structure enables a fusion branch and we add the Bi-directional Multi-step Propagation (BMP) strategy to it, which can not only retain the feature streams of the original RGB and depth branches but also fully utilize the feature flow of the fusion branch. There are three kinds of complementary attention modules that we have constructed. The RGB-D fusion module can effectively extract important features from the RGB and depth branch streams. The refinement module can reduce the loss of semantic information and the context aggregation module can help propagate and integrate information better. We train and evaluate our model on NYUDv2 and SUN-RGBD datasets, and prove that our model achieves state-of-the-art performances.     

A novel deep learning scheme for multi-condition remaining useful life prediction of rolling element bearings

The remaining useful life (RUL) prediction of a rolling element bearing is important for more reasonable maintenance of machinery and equipment. Generally, the information of a failure can hardly be acquired in advance while running and the degradation process varies in terms of different faults. Thus, fault identification is indispensable for a multi-condition RUL prediction, where, however, the fault identification and RUL prediction are separated in most studies. A new hybrid scheme is proposed in this paper for the multi-condition RUL prediction of rolling element bearings. The proposed scheme contains both classification and regression, where the 2D-DCNN based classifier and predictors are built concerning typical fault conditions of a bearing. For the online prediction, the raw signals are spanned in the time-frequency domain and then transferred into images as the input of the scheme. The classifier is used to monitor the vibration of rolling bearings for online fault recognition and excite the corresponding predictor for RUL prediction once a fault is detected. The output from the predictor is amended by the proposed adaptive delay correction method as the final prediction results. A demonstration is performed based on the XJTU-SY datasets and the results are compared with those from the state-of-the-art methods, which proves the superiority of the proposed scheme in improving the accuracy and linearity of RUL prediction. The time cost of the proposed online prediction scheme is also investigated and the results indicate high time effectiveness.     

基于混沌免疫网络的镍氢电池建模研究

针对电动汽车用镍氢电池组,提出利用计算智能算法训练的RBF网络实现电池组建模;首先采用免疫聚类的方法,通过对样本径基进行成分提取,并与并行免疫进化规划(PCEIP)相结合,形成一种更有效的RBF网络构造策略,然后基于PCIEP设计了改进的RBF网络的训练步骤;最后,在镍氢电池恒流放电和变功率放电工况下,以改进的RBF网络实现镍氢电池建模,验证建模的精度。     

On-demand multicast routing protocol with efficient route discovery

In this paper, we introduce an efficient route discovery mechanism to enhance the performance and multicast efficiency of On-Demand Multicast Routing Protocol (ODMRP). Our framework, called limited flooding ODMRP, improves multicasting mechanism by efficiently managing flooding mechanism based on delay characteristics of the contributing nodes. In our model, only the nodes that satisfy the delay requirements can flood the Join-Query messages. We model the contributing nodes as M/M/1 queuing systems. Our framework considers the significant parameters in delay analysis, including random packet arrival, service process, and random channel access in the relying nodes, and exhibits its best performance results under high traffic load. Simulation results reveal that limited flooding ODMRP drastically reduces the packet overhead under various simulation scenarios as compared to original ODMRP.     

Towards a theoretical framework of strategic decision, supporting capability and information sharing under the context of Internet of Things

The effective strategy of Internet of Things (IoT) can help firms to grasp the emerging opportunities from the IoT and then improve their competitive advantage. In this article, based on organizational capability perspective, we provide a theoretical framework which classifies IoT strategies into four archetypes from two dimensions of managers’ strategic intent and industrial driving force, and propose that market-based exploratory capabilities play a more important role for firms adopting get-ahead strategy, and market-based exploitative capabilities play a more important role for firms adopting catch-up strategy in market. The technology-based exploratory capabilities play a more important role for firms adopting get-ahead strategy in technology, and technology-based exploitative capabilities play a more important role for firms adopting catch-up strategy in technology. Especially, external industry information sharing more efficiently contributes to the enhancement of both market-based and technology-based exploratory capabilities, and internal industry information sharing more efficiently contributes to the enhancement of both market-based and technology-based exploitative capabilities.     

Optimal configuration of Energy-Efficient Ethernet

The IEEE 802.3az standard provides a new low power mode that Ethernet network interfaces can use to save energy when there is no traffic to transmit. Simultaneously with the final standard approval, several algorithms were proposed to govern the physical interface state transition between the normal active mode and the new low power mode. In fact, the standard leaves this sleeping algorithm unspecified to spur competition among different vendors and achieve the greatest energy savings. In this paper, we try to bring some light to the most well known sleeping algorithms, providing mathematical models for the expected energy savings and the average packet delay inflicted on outgoing traffic. We will then use the models to derive optimum configuration parameters for them under given efficiency constraints.     

分数阶Chen混沌系统同步及Multisim电路仿真

本文针对参数已知和未知的分数阶Chen混沌系统,研究其同步控制问题。利用分数阶系统稳定性理论,设计并实现了系统的反馈控制器;同时运用Multisim软件设计实现了分数阶系统同步的混沌电路,验证了所提出同步方法的有效性和可实现性。     

特高压直流送端系统的运行约束及新能源消纳挑战研究

针对特高压直流工程投运后电网特性的变化,分析了电力系统安全、经济运行面临的挑战及可采取的对策。首先在简要介绍直流系统故障的基础上,分别针对有功回退引起的暂态功角稳定问题与无功冗余造成的暂态过电压问题进行了理论分析,并根据陕西电网仿真计算结果进一步说明直流投运后对运行灵活性的制约。然后分析了运行灵活性下降对新能源消纳造成的影响,讨论了提高新能源消纳能力的对策。最后对所讨论问题进行归纳总结,并提出了未来工作与研究的展望。