化肥企业质检机构的管理

针对我国化肥生产企业质检机构的现状 ,结合国家相关政策的要求 ,就如何搞好化肥企业质检机构的管理提出了诸多指导性意见     

A novel self-adaptive extreme learning machine based on affinity propagation for radial basis function neural network

In this paper, a novel self-adaptive extreme learning machine (ELM) based on affinity propagation (AP) is proposed to optimize the radial basis function neural network (RBFNN). As is well known, the parameters of original ELM which developed by G.-B. Huang are randomly determined. However, that cannot objectively obtain a set of optimal parameters of RBFNN trained by ELM algorithm for different realistic datasets. The AP algorithm can automatically produce a set of clustering centers for the different datasets. According to the results of AP, we can, respectively, get the cluster number and the radius value of each cluster. In that case, the above cluster number and radius value can be used to initialize the number and widths of hidden layer neurons in RBFNN and that is also the parameters of coefficient matrix H of ELM. This may successfully avoid the subjectivity prior knowledge and randomness of training RBFNN. Experimental results show that the method proposed in this thesis has a more powerful generalization capability than conventional ELM for an RBFNN.     

Trusted Integrated Circuits: The Problem and Challenges

Hardware security has become more and more important in current information security architecture. Recently collected reports have shown that there may have been considerable hardware attacks prepared for possible military usage from all over the world. Due to the intrinsic difference from software security, hardware security has some special features and challenges. In order to guarantee hardware security, academia has proposed the concept of trusted integrated circuits, which aims at a secure circulation of IC design, manufacture and chip using. This paper reviews the main problems of trusted integrated circuits, and concludes four key domains of the trusted IC, namely the trusted IC design, trusted manufacture, trusted IP protection, and trusted chip authentication. The main challenges in those domains are also analyzed based on the current known techniques. Finally, the main limitations of the current techniques and possible future trends are discussed.     

一种关于模糊时间序列模型论域划分的多尺度比率算法

针对模糊时间序列研究中比率划分论域方法存在对非均匀数据划分效果不理想的缺陷, 提出一种基于模糊C 均值聚类(FCM) 算法的多尺度比率划分论域的方法. 首先利用FCM算法对样本数据进行分类; 然后计算各类数据的平均相对误差, 并基于各类的平均误差划分论域, 产生非等间隔的多尺度论域划分方法; 最后, 通过算例表明了多尺度比率论域划分方法的有效性.     

浅析渭河下游涉河桥梁现场监管要点

为有效把握现场监管的要点,进一步做好渭河下游涉河项目现场监管工作,本文结合渭河下游涉河桥梁现场监管工作实践,对涉河桥梁的承台、桥墩、梁底高程、围堰、施工便桥等现场监管要点进行分析梳理,并论述各个监管技术要点与河道管理的关系,提出现场监管单位根据监管要点进行监管的思路、内容及方法,对当前形势下,开展好渭河下游涉河项目现场监管有着现实的指导意义。可供涉河建设项目现场监管工作借鉴和参考。     

A Rough RBF Neural Network Based on Weighted Regularized Extreme Learning Machine

Adjusting parameters iteratively is a traditional way of training neural networks, and the Rough RBF Neural Networks (R-RBF-NN) follows the same idea. However, this idea has many disadvantages, for instance, the training accuracy and generalization accuracy etc. So how to change this condition is a hot topic in Academics. On the basis of Extreme Learning Machine (ELM), this paper proposes a Weighted Regularized Extreme Learning Machine (WRELM), taking into account both minimizing structured risk and weighted least-squares principle, to train R-RBF-NN. The traditional iterative training method is replaced by the minimal norm least-squares solution of general linear system. The method proposed in this paper, increasing controllability of the entire learning process and considering the structured risk and empirical risk, can improve the performance of learning and generalization. Experiments show that it can reach a very superior performance in both time and accuracy when WRELM trains the Rough RBF Neural Networks in pattern classification and function regression, especially in pattern classification, which can improve the generalization accuracy more than 3.36 % compared with ELM. Obviously, the performance of the method proposed in this paper is better than the traditional methods.     

Multi-secret visual cryptography with deterministic contrast

Multimedia Tools and Applications - The multi-secret visual cryptography scheme (MVCS) allows for the encryption of multiple secret images into a given image area. The previous works on MVCS with...     

Everything-as-a-service platform for on-demand virtual enterprises

While constructing virtual enterprises, it is crucial to flexibly integrate heterogeneous business resources and processes of different business partners and make them collaborate dynamically. Keeping involved IT systems or components as autonomous and loose-coupled services, the “Everything as a Service” concept supports flexible integration of heterogeneous applications. We adopt this concept and analyze the challenges in virtual enterprise construction, then propose a service platform for on-demand virtual enterprises. The platform supports flexible integration of networked resources, and facilitates virtual enterprise construction with business process utility, trusted service composition and data service centric business collaborations. At the end of the paper, together with a case study, experimental evaluations in contexts of concurrent multi-users are presented, showing the effectiveness and performance of the platform.     

变电站典型光通信模式研究

目前,通信条件已发生了革命性的变化,由早期的载波、微波和电缆等通信介质发展成为以光缆为主的通信网络.电力系统以OPGW光缆、ADSS光缆为主,已覆盖了几乎所有的输变电场所.因此,应建立与之适应的通信模式.通过研究现代通信条件、变电站通信的需求,提出了统一化的、简单的变电站通信模式.     

数字签名技术的应用

数字签名技术建立在公钥加密系统基础之上,可以检验数据传输过程中是否被篡改以及数据的真实性和完整性。利用其提供的安全保障机制,在某市自建的横向联网系统中实现了对交易报文在传递过程中的安全加密,从软件架构上进一步完善了系统的安全体系。