引入BL-Seq2seq模型进行负荷预测

短期负荷预测在电力系统运行和调度中起着重要作用,为了更好地提取数据中蕴含的有效信息,提升短期负荷预测精度,本文引入Seq2seq算法的注意力机制提出了多层Bi-LSTM的Seq2seq深度学习模型(BL-Seq2seq)实现短期用电负荷预测.其中Seq2seq的编码端由多层Bi-LSTM组成,将输入数据进行编码,并在网络末端输出编码后的最终状态;Seq2seq解码端为单层LSTM,它将编码端的最终状态作为初始输入状态,同时每一步的输出值作为下一步的输入值.利用用电负荷实测数据,基于Keras平台进行仿真,仿真结果表明,与多个经典的深度学习的短期用电负荷预测模型相比,所提BL-Seq2seq模型的预测误差明显降低,大大提升了短期用电负荷预测精度.     

SAR成像应用特征分析及硬件设计空间讨论

合成孔径雷达SAR是一种主动式的对地观测系统.近年来SAR逐渐朝着多平台化发展,陆续出现了在无人机、探测车等小型移动平台上.SAR成像是运行在SAR上的成像程序,由于新的特殊运行环境的出现、其对低能耗和高算力有了更严格的要求.如何针对特定的平台,提供高性能、低功耗的应用支持,便成为其核心要点.对SAR成像计算和访存等特征进行了分析,针对性地进行了程序优化并测试了该程序在x86平台上的性能,以获得可靠的性能参考.在此基础上,面向DSP+FFT加速器的硬件结构,构建了一个算力配比数学模型,为硬件设计提供解决方案.     

A brief review on α-zirconium phosphate intercalation compounds and nano-composites

The layer structured zirconium phosphate(Zr P) can be intercalated with atoms, molecules, small organic groups and even polymers. The structures and properties of the Zr P intercalation compounds can be deliberately tuned, leading to promising potential applications in many fields. This article provides a brief review on the experimental results of the Zr P intercalation compounds, with the focus on the polymer/a-zirconium phosphate (α-Zr P) nano-composites. The computer simulations of the Zr P intercalation compounds at the atomic level play a significant role in designing and understanding the properties of Zr P, and in the promotion of the applications of compounds.     

Evolution of insoluble eutectic Si particles in anodic oxidation films during adipic-sulfuric acid anodizing processes of ZL114A aluminum alloys

The effects of insoluble eutectic Si particles on the growth of anodic oxide films on ZL114A aluminum alloy substrates were in-vestigated by optical microscopy (OM) and scanning electron microscopy (SE...     

直齿轮精密塑性成形时齿面裂纹的产生机理及控制方法

本文通过对内齿轮缩挤成形工艺的有限元模拟 ,分析了直齿轮成形时齿面裂纹的产生机理 ,并从理论上进行了解释 ,进而提出了防止齿面裂纹产生的方法     

基于Windows数控系统的多线程实现

本文介绍了基于Windows平台数控系统的多线程的实现方法，着重阐述了数控系统多线程实现的线程创建、优先级设定和线程同步问题。     

Video summarization via minimum sparse reconstruction

The rapid growth of video data demands both effective and efficient video summarization methods so that users are empowered to quickly browse and comprehend a large amount of video content. In this paper, we formulate the video summarization task with a novel minimum sparse reconstruction (MSR) problem. That is, the original video sequence can be best reconstructed with as few selected keyframes as possible. Different from the recently proposed convex relaxation based sparse dictionary selection method, our proposed method utilizes the true sparse constraint L₀ norm, instead of the relaxed constraint _L2,1$L_{2,1}$ norm, such that keyframes are directly selected as a sparse dictionary that can well reconstruct all the video frames. An on-line version is further developed owing to the real-time efficiency of the proposed MSR principle. In addition, a percentage of reconstruction (POR) criterion is proposed to intuitively guide users in obtaining a summary with an appropriate length. Experimental results on two benchmark datasets with various types of videos demonstrate that the proposed methods outperform the state of the art.     

Accurate sensing of scene geo-context via mobile visual localization

Image geo-tagging has drawn a great deal of attention in recent years. The geographic information associated with images can be used to promote potential applications such as location recognition or virtual navigation. In this paper, we propose a novel approach for accurate mobile image geo-tagging in urban areas. The approach is able to provide a comprehensive set of geo-context information based on the current image, including the real location of the camera and the viewing angle, as well as the location of the captured scene. Moreover, the parsed building facades and their geometric structures can also be estimated. First, for the image to be geo-tagged, we perform partial duplicate image retrieval to filter crowd-sourced images capturing the same scene. We then employ the structure-from-motion technique to reconstruct a sparse 3D point cloud of the scene. Meanwhile, the geometric structure of the query image is analyzed to extract building facades. Finally, by combining the reconstructed 3D scene model and the extracted structure information, we can register the camera location and viewing direction to a real-world map. The captured building location and facade orientation are also aligned. The effectiveness of the proposed system is demonstrated by experiment results.     

基于事件逻辑的改进Needham-Schroeder协议安全性证明

安全协议是现代网络安全的基础,密码协议的安全性证明是一个挑战性的问题。事件逻辑是一种描述分布式系统中状态迁移的形式化方法,用于刻画安全协议的形式化描述,是定理证明的基础。用事件序语言、事件类和一个表示随机数、密钥、签名和密文的原子类,给出身份认证协议可以被形式化定义和强认证性证明理论。利用该理论对增加时间戳的Needham-Schroeder协议安全性进行证明,证明改进的Needham-Schroeder协议是安全的。此理论适用于类似复杂协议形式化分析与验证。     

运用SPIN对开放授权协议OAuth 2.0的分析与验证

OAuth 2.0协议是一种开放授权协议,主要用于解决用户账号关联与资源共享问题。但是,其弱安全性导致各网络公司海量用户信息泄露,且OAuth 2.0传输数据采用的https通道效率低下,成为黑客攻击对象。提出采用http通道传输OAuth 2.0协议数据,基于Promale语言及Dolev-Yao攻击者模型对OAuth 2.0协议建模,运用SPIN进行模型检测。形式化分析结果表明,采用公钥加密体系对OAuth 2.0协议进行加密不安全。上述建模方法对类似的授权协议形式化分析有重要借鉴意义。